U.S. patent number 9,983,183 [Application Number 15/297,693] was granted by the patent office on 2018-05-29 for highly selective nanostructure sensors and methods of detecting target analytes.
This patent grant is currently assigned to George Mason University, The George Washington University, The United States of America, as represented by the Secretary of Commerce, University of Maryland, College Park. The grantee listed for this patent is George Mason University, The George Washington University, The United States of America, as Represented by the Secretary of Commerce, University of Maryland, College Park. Invention is credited to Geetha Aluri, Ritu Bajpai, Albert V. Davydov, Ratan Debnath, Guannan Liu, Abhishek Motayed, Vladimir P. Oleshko, Mulpuri V. Rao, Brian Thomson, Baomei Wen, Ting Xie, Mona E. Zaghloul.
United States Patent |
9,983,183 |
Motayed , et al. |
May 29, 2018 |
Highly selective nanostructure sensors and methods of detecting
target analytes
Abstract
A nanostructure sensing device comprises a semiconductor
nanostructure having an outer surface, and at least one of metal or
metal-oxide nanoparticle clusters functionalizing the outer surface
of the nanostructure and forming a photoconductive
nanostructure/nanocluster hybrid sensor enabling light-assisted
sensing of a target analyte.
Inventors: |
Motayed; Abhishek (Rockville,
MD), Aluri; Geetha (Clifton Park, NY), Davydov; Albert
V. (North Potomac, MD), Rao; Mulpuri V. (Fairfax
Station, VA), Oleshko; Vladimir P. (Gaithersburg, MD),
Bajpai; Ritu (Santa Clara, CA), Zaghloul; Mona E.
(Bethesda, MD), Thomson; Brian (Washington, DC), Wen;
Baomei (Gaithersburg, MD), Xie; Ting (Burtonsville,
MD), Liu; Guannan (Portland, OR), Debnath; Ratan
(Damascus, MD) |
Applicant: |
Name |
City |
State |
Country |
Type |
University of Maryland, College Park
The United States of America, as Represented by the Secretary of
Commerce
George Mason University
The George Washington University |
College Park
Washington
Fairfax
Washington |
MD
DC
VA
DC |
US
US
US
US |
|
|
Assignee: |
University of Maryland, College
Park (College Park, MD)
The United States of America, as represented by the Secretary of
Commerce (Washington, DC)
George Mason University (Fairfax, VA)
The George Washington University (Washington, DC)
|
Family
ID: |
58052930 |
Appl.
No.: |
15/297,693 |
Filed: |
October 19, 2016 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20170038326 A1 |
Feb 9, 2017 |
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Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
Issue Date |
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13861962 |
Apr 12, 2013 |
9476862 |
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61775305 |
Mar 8, 2013 |
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61730865 |
Nov 28, 2012 |
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61625511 |
Apr 17, 2012 |
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61623957 |
Apr 13, 2012 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N
27/127 (20130101); G01N 33/0054 (20130101); G01N
33/004 (20130101); G01N 33/0037 (20130101); G01N
33/005 (20130101); G01N 33/0057 (20130101); G01N
33/0042 (20130101); G01N 33/0049 (20130101); G01N
33/0047 (20130101); G01N 33/0031 (20130101); G01N
33/0044 (20130101); Y02A 50/20 (20180101) |
Current International
Class: |
G01N
21/75 (20060101); G01N 33/00 (20060101); G01N
27/12 (20060101) |
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|
Primary Examiner: White; Dennis
Attorney, Agent or Firm: Schrot; William C. AuerbachSchrot
LLC
Government Interests
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
This work was supported by the National Science Foundation (NSF)
under ECCS-0901712 grant, by the Defense Threat Reduction Agency
(DTRA) under HDTRA11010107, and by the National Institute of
Standards and Technology (NIST) under SB134110SE0579 and
SB134111SE0814. The US government has certain rights in this
invention.
Parent Case Text
CROSS-REFERENCE TO RELATED APPLICATIONS
This application is a continuation-in-part of U.S. patent
application Ser. No. 13/861,962 (filed Apr. 12, 2013), which is
based on U.S. Provisional Patent Application Ser. No. 61/623,957
(filed Apr. 13, 2012), Application Ser. No. 61/625,511 (filed Apr.
17, 2012), Application Ser. No. 61/730,865 (filed Nov. 28, 2012),
and Application Ser. No. 61/775,305 (filed Mar. 8, 2013), which
applications are all incorporated herein by reference in their
entireties and to which priority is claimed.
Claims
What is claimed is:
1. A multi-analyte sensor, comprising: a semiconductor
nanostructure having an outer surface; first nanoparticles of
metal-oxide, said first nanoparticles functionalizing said outer
surface of said semiconductor nanostructure, said first
nanoparticles having a first adsorption profile; and second
nanoparticles of metal or metal-oxide, said second nanoparticles
functionalizing said outer surface of said semiconductor structure,
said second nanoparticles having a second adsorption profile,
wherein a target analyte preferentially adsorbs on one of said
first or second nanoparticles and thereby enables detection of said
target analyte, and an interfering analyte preferentially adsorbs
on the other of said first or second nanoparticles.
2. The sensor of claim 1, wherein said sensor exhibits a change in
output upon detection of said target analyte, said output selected
from the group consisting of current, voltage and resistance.
3. The sensor of claim 1, wherein said semiconductor nanostructure
comprises a plurality of segments coupled in series or in parallel
to define a current path.
4. The sensor of claim 1, wherein said semiconductor nanostructure
comprises a material selected from the group consisting of gallium
nitride (GaN), indium nitride (InN), aluminum gallium nitride
(ALGaN), zinc oxide (ZnO), and Indium arsenide (InAs).
5. The sensor of claim 1, wherein said first nanoparticles comprise
one or more metal-oxide nanoparticles selected from the group
consisting of titanium dioxide (TiO.sub.2) nanoparticles, tin oxide
(SnO.sub.2) nanoparticles, zinc oxide (ZnO) nanoparticles, nickel
oxide (NiO) nanoparticles, copper oxide (Cu.sub.xO.sub.x)
nanoparticles, cobalt oxide (Co.sub.xO.sub.x) nanoparticles, iron
oxide (Fe.sub.xO.sub.x) nanoparticles, zinc magnesium oxide
(Zn.sub.1-xMg.sub.xO) nanoparticles, magnesium oxide (MgO)
nanoparticles, vanadium oxide (V.sub.xO.sub.x) nanoparticles,
lanthanum oxide (La.sub.2O.sub.3) nanoparticles, zirconium oxide
(ZrO.sub.2) nanoparticles, aluminum oxide (Al.sub.2O.sub.3)
nanoparticles, strontium oxide (SrO) nanoparticles, lanthanum oxide
(La.sub.2O.sub.3) nanoparticles, cerium oxide (Ce.sub.xO.sub.x)
nanoparticles, praseodymium oxide (Pr.sub.xO.sub.x) nanoparticles,
promethium oxide (Pm.sub.2O.sub.3) nanoparticles, samarium oxide
(Sm.sub.2O.sub.3) nanoparticles, europium oxide (Eu.sub.2O.sub.3)
nanoparticles, gadolinium oxide (Gd.sub.2O.sub.3) nanoparticles,
terbium oxide (Tb.sub.xO.sub.x) nanoparticles, dysprosium oxide
(Dy.sub.2O.sub.3) nanoparticles, holmium oxide (Ho.sub.2O.sub.3)
nanoparticles, erbium oxide (Er.sub.2O.sub.3) nanoparticles,
thulium oxide (Tm.sub.2O.sub.3) nanoparticles, ytterbium oxide
(Yb.sub.2O.sub.3) nanoparticles, and lutetium oxide
(Lu.sub.2O.sub.3) nanoparticles.
6. The sensor of claim 1, wherein said second nanoparticles
comprise one or more metal-oxide nanoparticles selected from the
group consisting of titanium dioxide (TiO.sub.2) nanoparticles, tin
oxide (SnO.sub.2) nanoparticles, zinc oxide (ZnO) nanoparticles,
nickel oxide (NiO) nanoparticles, copper oxide (Cu.sub.xO.sub.x)
nanoparticles, cobalt oxide (Co.sub.xO.sub.x) nanoparticles, iron
oxide (Fe.sub.xO.sub.x) nanoparticles, zinc magnesium oxide
(Zn.sub.1-xMg.sub.xO) nanoparticles, magnesium oxide (MgO)
nanoparticles, vanadium oxide (V.sub.xO.sub.x) nanoparticles,
lanthanum oxide (La.sub.2O.sub.3) nanoparticles, zirconium oxide
(ZrO.sub.2) nanoparticles, aluminum oxide (Al.sub.2O.sub.3)
nanoparticles, strontium oxide (SrO) nanoparticles, lanthanum oxide
(La.sub.2O.sub.3) nanoparticles, cerium oxide (Ce.sub.xO.sub.x)
nanoparticles, praseodymium oxide (Pr.sub.xO.sub.x) nanoparticles,
promethium oxide (Pm.sub.2O.sub.3) nanoparticles, samarium oxide
(Sm.sub.2O.sub.3) nanoparticles, europium oxide (Eu.sub.2O.sub.3)
nanoparticles, gadolinium oxide (Gd.sub.2O.sub.3) nanoparticles,
terbium oxide (Tb.sub.xO.sub.x) nanoparticles, dysprosium oxide
(Dy.sub.2O.sub.3) nanoparticles, holmium oxide (Ho.sub.2O.sub.3)
nanoparticles, erbium oxide (Er.sub.2O.sub.3) nanoparticles,
thulium oxide (Tm.sub.2O.sub.3) nanoparticles, ytterbium oxide
(Yb.sub.2O.sub.3) nanoparticles, and lutetium oxide
(Lu.sub.2O.sub.3) nanoparticles.
7. The sensor of claim 1, wherein said second nanoparticles
comprise one or more metal nanoparticles selected from the group
consisting of lithium nanoparticles, sodium nanoparticles,
potassium nanoparticles, rubidium nanoparticles, cesium
nanoparticles, francium nanoparticles, beryllium nanoparticles,
magnesium nanoparticles, calcium nanoparticles, strontium
nanoparticles, barium nanoparticles, radium nanoparticles, aluminum
nanoparticles, gallium nanoparticles, indium nanoparticles, tin
nanoparticles, thallium nanoparticles, lead nanoparticles, bismuth
nanoparticles, scandium nanoparticles, titanium nanoparticles,
vanadium nanoparticles, chromium nanoparticles, manganese
nanoparticles, iron nanoparticles, cobalt nanoparticles, nickel
nanoparticles, copper nanoparticles, zinc nanoparticles, yttrium
nanoparticles, zirconium nanoparticles, niobium nanoparticles,
molybdenum nanoparticles, technetium nanoparticles, ruthenium
nanoparticles, rhodium nanoparticles, palladium nanoparticles,
silver nanoparticles, cadmium nanoparticles, lanthanum
nanoparticles, hafnium nanoparticles, tantalum nanoparticles,
tungsten nanoparticles, rhenium nanoparticles, osmium
nanoparticles, iridium nanoparticles, platinum nanoparticles, gold
nanoparticles, mercury nanoparticles, and combinations or alloys
thereof.
8. The sensor of claim 1, wherein said sensor is capable of
detecting said target analyte at a temperature of less than about
100.degree. C.
9. The sensor of claim 8, wherein said sensor is capable of
detecting said target analytes at a temperature of between about
18.degree. C. and about 24.degree. C.
10. The sensor of claim 1, wherein said target analyte is a
gas.
11. The sensor of claim 10, wherein said gas is selected from the
group consisting of NO.sub.x, H.sub.2, CH.sub.4, CO.sub.2, CO,
NH.sub.3, CO, O.sub.2, SO.sub.x, H.sub.2S, Cl.sub.2, and HCN.
12. The sensor of claim 11, wherein said gas is O.sub.2.
13. The sensor of claim 11, wherein said gas is CO.sub.2.
14. The sensor of claim 1, wherein said target analyte is a
volatile organic compound (VOC).
15. The sensor of claim 14, wherein said VOC is selected from the
group consisting of benzene, toluene, ethylbenzene, xylene,
chlorobenzene, formaldehyde benzene, formaldehyde, methanol,
ethanol, isopropanol, hexane, acetone, tetrachloroethylene, methyl
tert-butyl ether, methylene chloride, D-limonene, methylene
chloride, an alkane, a cycloalkane, an alkene, a ketone, a silane,
a siloxane, and mixtures thereof.
16. The sensor of claim 15, wherein said VOC is an alkane selected
from the group consisting of propane, butane, methane, ethane,
pentane and hexane.
17. The sensor of claim 1, wherein said target analyte is a
chemical warfare agent (CWA).
18. The sensor of claim 17, wherein said CWA is selected from the
group consisting of tabun (GA), sarin (GB), soman (GD), cyclosarin
(GF), sulfur mustard (HD), and nitrogen mustard (HN).
19. The sensor of claim 17, wherein said CWA is a simulant chemical
selected from the group consisting of dimethyl methylphosphonate
(DMMP) and triethyl phosphonate (TEP).
20. The sensor of claim 1, wherein said sensor exhibits altered
conductivity upon exposure to said target analyte in the presence
of UV excitation.
21. The sensor of claim 1, further comprising: a substrate having
an upper surface, said semiconductor nanostructure disposed on said
upper surface of said substrate; and a microheater disposed on said
upper surface of said substrate and configured to stabilize said
semiconductor nanostructure in conditions of variable humidity or
temperature.
22. The sensor of claim 21, further comprising a temperature and
humidity sensing element disposed on said upper surface of said
substrate.
23. The sensor of claim 1, wherein a concentration of said target
analyte is between about 1 parts per million and about 50 parts per
billion.
24. The sensor of claim 1, wherein said sensor has a response and
recovery time of less than about 180 seconds.
Description
FIELD OF THE INVENTION
The present invention relates to a sensing device including a
semiconductor nanostructure and at least one of metal or
metal-oxide nanoparticles functionalizing the nanostructure and
forming a hybrid sensor that enables light-assisted sensing of a
target analyte.
BACKGROUND OF THE INVENTION
Detection of chemical species in air, such as industrial
pollutants, poisonous gases, chemical fumes, and volatile organic
compounds (VOCs), is vital for the health and safety of communities
around the world (see Watson J and Ihokura K (1999) Special issue
on Gas-Sensing Materials, Mater. Res. Soc. Bull. 24:14). The
development of reliable, portable gas sensors that can detect
harmful gases in real-time with high sensitivity and selectivity is
therefore extremely important (Wilson D M et al. (2001) "Chemical
Sensors for Portable, Handheld Field Instruments," IEEE Sensors
Journal 1:256-274; Eranna G et al. (2004) "Oxide Materials for
Development of Integrated Gas Sensors--A Comprehensive
Review/Integrated Gas Sensors--A Comprehensive Review," Critical
Reviews in Solid State and Material Sciences 29:111-188).
Due to their small size, ease of deployment, and low-power
operation, solid-state thin film sensors are favored over
analytical techniques such as optical and mass spectroscopy, and
gas chromatography for real-time environmental monitoring (Wilson D
M et al. (2001), supra, IEEE Sensor Journal 1:256-274; Shimizu Y
and Egashira M (1999) "Basic aspects and Challenges of
Semiconductor Gas Sensors," Mater. Res. Soc. Bull. 24:18; Sze S M
(1994) Semiconductor Sensors 1.sup.st ed, Willey; New York).
Selectivity, which is a sensor's ability to discriminate between
the components of a gas mixture and provide detection signal for
the component of interest, is an important consideration for the
sensor's real-life applicability. Conventional metal-oxide based
thin film sensors, despite decades of research and development
(Brattain J B W H (1952) "Surface properties of germanium," Bell.
Syst. Tech. Journal 32:1; Azad A M et al. (1992) "Solid-State
Sensors: A Review," J. Electrochem. Soc. 139(12):3690-3704), still
lack selectivity for different species and typically require high
working temperatures (Meixner H and Lampe U (1996) "Metal oxide
sensors," Sens. and Actuators B 33:198-202; Nicoletti S et al.
(2003) "Use of Different Sensing Materials and Deposition
Techniques for Thin-Film Sensors to Increase Sensitivity and
Selectivity," IEEE Sensors Journal 3:454-459; Demarne V and
Sanjines R (1992) Gas Sensors-Principles, Operation and
Developments ed. G. Sberveglieri, Kluwer Academic, Netherlands). As
such, the usability of such conventional sensors is severely
limited and poses long-term reliability problems.
For a chemical sensor, the active surface area is an important
factor for determining its detection limits or sensitivity. It is
known that the electrical properties of nanowires (NWs) change
significantly in response to their environments due to their high
surface to volume ratio (Cui Y et al. (2001), supra, Science
293:1289-1292; Zhang D et al. (2004) "Detection of NO.sub.2 down to
ppb levels using individual and multiple In.sub.2O.sub.3 nanowire
devices," Nano. Lett. 4:1919-1924; Kong J et al. (2000) "Nanotube
Molecular Wires as Chemical Sensors," Science 287:622-625; Comini E
et al. (2002) "Stable and highly sensitive gas sensors based on
semiconducting oxide nanobelts," Appl. Phys. Lett. 81:1869). NWs
are therefore well suited for direct measurement of changes in
their electrical properties (e.g. conductance/resistance,
impedance) when exposed to various analytes. Substantial research
has demonstrated the enhanced sensitivity, reactivity, and
catalytic efficiency of the nanoscale structures (Cui Y et al.
(2001), supra, Science 293:1289; Li C et al. (2003)
"In.sub.2O.sub.3 nanowires as chemical sensors," Appl. Phys. Lett.
8:1613; Wan Q et al. (2004) "Fabrication and ethanol sensing
characteristics of ZnO nanowire gas sensors," Appl. Phys. Lett.
84:3654; Wang C et al. (2005) "Detection of H.sub.2S down to ppb
levels at room temperature using sensors based on ZnO nanorods,"
Sens. and Actuators B 113:320-323; Wang H T et al. (2005)
"Hydrogen-selective sensing at room temperature with ZnO nanorods,"
Appl. Phys. Lett. 86:243503; Raible I et al. (2005) "V.sub.2O.sub.5
nanofibers: novel gas sensors with extremely high sensitivity and
selectivity to amines," Sens. and Actuators B 106:730-735; McAlpine
M C et al. (2007) "Highly ordered nanowire arrays on plastic
substrates for ultrasensitive flexible chemical sensors," Nat Mater
6:379-384).
There have been attempts to demonstrate sensors based on
nanotube/nanowire decorated with nanoparticles of metal and
metal-oxides. For example, Leghrib et al. reported gas sensors
based on multiwall carbon nanotubes (CNTs) decorated with tin-oxide
(SnO.sub.2) nanoclusters for detection of NO and CO (see Leghrib R
et al. (2010) "Gas sensors based on multiwall carbon nanotubes
decorated with tin oxide nanoclusters," Sens. and Actuators B:
Chemical 145:411-416). Using mixed SnO.sub.2/TiO.sub.2 included
with CNTs, Duy et al. demonstrated ethanol sensing at a temperature
of 250.degree. C. (Duy N V et al. (2008) "Mixed SnO.sub.2/TiO.sub.2
Included with Carbon Nanotubes for Gas-Sensing Application," J.
Physica E 41:258-263). Balazsi et al. fabricated hybrid composites
of hexagonal WO.sub.3 powder with metal decorated CNTs for sensing
NO.sub.2 (Balazsi C et al. (2008) "Novel hexagonal WO.sub.3
nanopowder with metal decorated carbon nanotubes as NO.sub.2 gas
sensor," Sensors and Actuators B: Chemical 133:151-155). Kuang et
al. demonstrated an increase in the sensitivity of SnO.sub.2
nanowire sensors to H.sub.2S, CO, and CH.sub.4 by surface
functionalization with ZnO or NiO nanoparticles (Kuang Q et al.
(2008) "Enhancing the photon-and gas-sensing properties of a single
SnO.sub.2 nanowire based nanodevice by nanoparticle surface
functionalization," J. Phys. Chem. C 112:11539-11544). ZnO NWs
decorated with Pt nanoparticles were utilized by Zhang et al.,
showing that the response of Pt nanoparticles decorated ZnO NWs to
ethanol is three times higher than that of bare ZnO NWs (Zhang Y et
al. (2010) "Decoration of ZnO nanowires with Pt nanoparticles and
their improved gas sensing and photocatalytic performance,"
Nanotechnology 21:285501). Chang et al. showed that by adsorption
of Au nanoparticles on ZnO NWs, the sensor sensitivity to CO gas
could be enhanced significantly (Chang S-J et al. (2008) "Highly
sensitive ZnO nanowire CO sensors with the adsorption of Au
nanoparticles," Nanotechnology 19:175502). Dobrokhotov et al.
constructed a chemical sensor from mats of GaN NWs decorated with
Au nanoparticles and tested their sensitivity to N.sub.2 and
CH.sub.4 (Dobrokhotov V et al. (2006) "Principles and mechanisms of
gas sensing by GaN nanowires functionalized with gold
nanoparticles," J. Appl. Phys 99:104302). GaN NWs coated with Pd
nanoparticles were employed for the detection of H.sub.2 in N.sub.2
at 300K by Lim et al. (Lim W et al. (2008) "Room temperature
hydrogen detection using Pd-coated GaN nanowires," Appl. Phys.
Lett. 93:072109).
Although such results demonstrate the potentials of the
nanowire-nanocluster based hybrid sensors, fundamental challenges
and deficiencies in such prior attempts remain. Most of the results
provide for mats of nanowires. Although such mats may increase
sensitivity, the complex nature of inter-wire conduction makes
interpreting the results difficult. Also, room-temperature
operation of such previous sensors has not been demonstrated, and
the selectivity is shown for only a very limited number of
chemicals. Conventional sensor devices require high operating
temperatures (.gtoreq.250.degree. C.) and large response times
(more than 5 minutes). Indeed, such temperature-assisted sensors
typically provide for an integrated heater for the device. Further,
the reported sensitivities of such conventional devices were quite
low even with long response times. Further, such conventional
devices typically do not provide for air as the carrier gas.
However, the ability of a sensor to detect chemicals in air is what
ultimately determines its usability in real-life.
Thus, such demonstrations have resulted in poor selectivity of
known chemical sensors, and therefore have not resulted in
commercially viable gas sensors. For real-world applications,
selectivity between different classes of compounds (such as between
aromatic compounds and alcohols) is highly desirable. For example,
the threat of terrorism and the need for homeland security call for
advanced technologies to detect concealed explosives safely and
efficiently. Detecting traces of explosives is challenging,
however, because of the low vapor pressures of most explosives
(Moore, D S (2004) "Instrumentation for trace detection of high
explosives," Review of Scientific Instruments 75(8):2499-2512;
Yinon J (2002) "Field detection and monitoring of explosives," TrAC
Trends in Analytical Chemistry 21(4):292-301; Senesac L. and
Thundat T G (2008) "Nanosensors for trace explosive detection,"
Materials Today 11(3):28-36. Moreover, the difficulty of explosive
detection is aggravated by the noisy environment which masks the
signal from the explosive, the potential for high false alarms, and
the need to determine a threat quickly. As such, trained canine
teams remain the most reliable means of detecting explosive vapors
to date; however, dogs are expensive to train and tire easily.
An ideal chemical sensor would be able to distinguish between the
individual analytes belonging to a particular class of compounds,
e.g. detection of the presence of benzene or toluene in the
presence of other aromatic compounds, detection of a particular
explosive compound, detection of a particular alcohol, etc. This is
extremely challenging as most semiconductor-based sensors use
metal-oxides (such as SnO.sub.2, In.sub.2O.sub.3, ZnO) as the
active elements, which are limited due to the non-selective nature
of the surface adsorption sites. The surface/adsorbate interactions
of conventional sensor structures are limited and non-specific.
Thus, conventional sensor devices lack the same selectivity as
their bulk-counterpart devices.
Accordingly, there is a need for a nanostructure sensor device that
solves one or more of the deficiencies of conventional devices.
SUMMARY OF THE INVENTION
The present invention is directed to highly selective and sensitive
sensor devices including semiconductor nanostructures decorated
with metal and/or metal-oxide nanoclusters or particles. The
disclosed sensors provide numerous advantages over conventional
sensors including: 1) light-induced room-temperature sensing as
opposed to thermally induced sensing, providing for reliable
operation at low-power, longer lifetime, and fast response/recovery
time; 2) excellent selectivity of sensing of selected compounds
(e.g., sensors able to distinguish toluene from other aromatic
compounds); 3) wide sensing range (50 ppb-1%); 4) fast response and
recovery; and 5) reliable and repeatable operation.
According to implementations of the present invention, hybrid
chemiresistive architectures utilizing nanoengineered wide-bandgap
semiconductor backbone functionalized with multicomponent
photocatalytic nanoclusters of metal-oxides and/or metals are
provided. Such implementations, e.g. providing for chip scale
hybrid sensor architecture backbones, are particularly suitable for
mass production employing industry standard fabrication techniques,
such as for commercial applications. The sensors operate at
room-temperature via photoenabled sensing, and utilize standard
microfabrication techniques. Thus, economical, multianalyte
single-chip sensors are achieved.
According to embodiments of the present invention, the disclosed
semiconductor nanostructures exhibit relatively inactive surface
properties (i.e., with little or no chemiresistive sensitivity to
different classes of organic vapors). The nanostructures are
functionalized with analyte-dependent active metal-oxides and/or
metals. Photoconductive metal-oxide-semiconductors may be utilized
as a functionalizing material due to their active surface
properties and light-assisted sensing operation. Unlike most
metal-oxide-based sensors that operate at high temperatures, the
photoconductive hybrid sensor devices of the present invention
enable rapid light-assisted sensing at temperatures well below
100.degree. C., and in particular at temperatures between about
10.degree. C. and 100.degree. C., including at room temperature
(e.g., between about 18.degree. C. and about 24.degree. C.). Thus,
the disclosed sensors operate at temperatures well below that
required by conventional oxide sensors (e.g., requiring sensing
temperatures higher than 100.degree. C.), thereby providing rapid
sensing capabilities at room temperature assisted by UV light
illumination.
According to one embodiment, a multi-analyte sensor comprises a
substrate having an upper surface, a semiconductor nanostructure
having an outer surface and disposed on the upper surface of the
substrate, first metal-oxide nanoparticles functionalizing the
outer surface of the semiconductor nanostructure and enabling
detection of a target analyte in the presence of light, the first
metal-oxide nanoparticles have a first adsorption profile, and
second metal nanoparticles functionalizing the outer surface of the
semiconductor structure. The second metal nanoparticles have a
second adsorption profile. The target analyte preferentially
adsorbs on the first metal-oxide, and an interfering analyte
preferentially adsorbs on the second metal nanoparticles. The
sensor exhibits a change in output upon detection of the target
analyte, the output selected from the group consisting of current,
voltage and resistance.
The disclosed sensors enable detection of the target analyte within
various carrier gases, including air, nitrogen or argon. The
semiconductor nanostructure may comprise gallium nitride (GaN),
indium nitride (InN), aluminum gallium nitride (ALGaN), zinc oxide
(ZnO), Indium arsenide (InAs). The metal-oxide nanoparticles may
comprise one or more nanoparticles selected from the group
consisting of titanium dioxide (TiO.sub.2) nanoparticles, tin oxide
(SnO.sub.2) nanoparticles, zinc oxide (ZnO) nanoparticles, nickel
oxide (NiO) nanoparticles, copper oxide (Cu.sub.xO.sub.x)
nanoparticles, cobalt oxide (Co.sub.xO.sub.x) nanoparticles, iron
oxide (Fe.sub.xO.sub.x) nanoparticles, zinc magnesium oxide
(Zn.sub.1-xMg.sub.xO) nanoparticles, magnesium oxide (MgO)
nanoparticles, vanadium oxide (V.sub.xO.sub.x) nanoparticles,
lanthanum oxide (La.sub.2O.sub.3) nanoparticles, zirconium oxide
(ZrO.sub.2) nanoparticles, aluminum oxide (Al.sub.2O.sub.3)
nanoparticles, strontium oxide (SrO) nanoparticles, lanthanum oxide
(La.sub.2O.sub.3) nanoparticles, cerium oxide (Ce.sub.xO.sub.x)
nanoparticles, praseodymium oxide (Pr.sub.xO.sub.x) nanoparticles,
promethium oxide (Pm.sub.2O.sub.3) nanoparticles, samarium oxide
(Sm.sub.2O.sub.3) nanoparticles, europium oxide (Eu.sub.2O.sub.3)
nanoparticles, gadolinium oxide (Gd.sub.2O.sub.3) nanoparticles,
terbium oxide (Tb.sub.xO.sub.x) nanoparticles, dysprosium oxide
(Dy.sub.2O.sub.3) nanoparticles, holmium oxide (Ho.sub.2O.sub.3)
nanoparticles, erbium oxide (Er.sub.2O.sub.3) nanoparticles,
thulium oxide (Tm.sub.2O.sub.3) nanoparticles, ytterbium oxide
(Yb.sub.2O.sub.3) nanoparticles, and lutetium oxide
(Lu.sub.2O.sub.3) nanoparticles.
The metal nanoparticles may comprise one or more nanoparticles
selected from the group consisting of lithium nanoparticles, sodium
nanoparticles, potassium nanoparticles, rubidium nanoparticles,
cesium nanoparticles, francium nanoparticles, beryllium
nanoparticles, magnesium nanoparticles, calcium nanoparticles,
strontium nanoparticles, barium nanoparticles, radium
nanoparticles, aluminum nanoparticles, gallium nanoparticles,
indium nanoparticles, tin nanoparticles, thallium nanoparticles,
lead nanoparticles, bismuth nanoparticles, scandium nanoparticles,
titanium nanoparticles, vanadium nanoparticles, chromium
nanoparticles, manganese nanoparticles, iron nanoparticles, cobalt
nanoparticles, nickel nanoparticles, copper nanoparticles, zinc
nanoparticles, yttrium nanoparticles, zirconium nanoparticles,
niobium nanoparticles, molybdenum nanoparticles, technetium
nanoparticles, ruthenium nanoparticles, rhodium nanoparticles,
palladium nanoparticles, silver nanoparticles, cadmium
nanoparticles, lanthanum nanoparticles, hafnium nanoparticles,
tantalum nanoparticles, tungsten nanoparticles, rhenium
nanoparticles, osmium nanoparticles, iridium nanoparticles,
platinum nanoparticles, gold nanoparticles, mercury nanoparticles,
and combinations or alloys thereof.
In disclosed embodiments, the sensors are capable of detecting a
target analyte within a wide temperature range and/or within a wide
humidity range. In addition, the disclosed sensors are capable of
detecting a target analyte at a temperature of less than about
100.degree. C. In some implementations, the sensors are capable of
detecting a target analyte at room temperature (e.g., between about
18.degree. C. and about 24.degree. C.). In some implementations,
the target analyte comprises a gas (e.g., NO.sub.2, H.sub.2,
CH.sub.4, CO.sub.2, CO, NH.sub.3, O.sub.2, SO.sub.x, H.sub.2S,
Cl.sub.2, HCl and/or HCN). In some implementations, the target
analyte is an alcohol vapor (e.g., methanol, ethanol, n-propanol,
isopropanol, n-butanol, and isobutanol). In other embodiments, the
target analyte is a volatile organic compound (VOC) (e.g., benzene,
toluene, ethylbenzene, xylene, chlorobenzene, formaldehyde benzene,
formaldehyde, methanol, ethanol, isopropanol, hexane, acetone,
tetrachloroethylene (TCE), MTBE, methylene chloride, d-limonene,
methylene chloride, an alkane (e.g., propane, butane), a ketone, a
silane, a siloxane, and mixtures such as diesel/gasoline vapor). In
other embodiments, the target analyte comprises a chemical warfare
agent (CWA) (e.g., tabun (GA), sarin (GB), soman (GD), cyclosarin
(GF), sulfur mustard (HD), nitrogen mustard (HN)), or another
simulant chemical (e.g., Dimethyl methylphosphonate (DMMP),
Triethyl phosphonate (TEP)).
The disclosed sensors are capable of detecting the target analyte
at a concentration of less than about 1%. In some implementations,
the concentration of the target analyte detected is between about 1
parts per million and about 50 parts per billion. In addition, the
disclosed sensors are capable of detecting humidity from between
about 0% to about 100% relative humidity (RH). In disclosed
embodiments, the sensing device has a response and recovery time of
less than about 180 seconds, preferably less than about 75
seconds.
The present invention is also directed to a nanostructure sensing
device comprising a semiconductor nanostructure having an outer
surface, and at least one of metal or metal-oxide nanoparticle
clusters functionalizing the outer surface of the nanostructure.
The dimensions and overall length of the sensing device may vary
(e.g., from nanometer to centimeter scale).
In some embodiments, the sensing device comprises a chip-scale
package having dimensions of less than about 10 mm by 10 mm, e.g.,
about 4 mm by 4 mm or smaller. Thus, the sensor devices of the
present invention are suitable for wearables and/or compact
applications, and also reliable and robust and thus suitable for
industrial applications and/or extreme conditions. The architecture
may provide for a single sensing device or multiple sensing
devices, e.g. connected in series or parallel. The resulting
structure forms a photoconductive nanostructure/nanocluster hybrid
sensor enabling light-assisted sensing of a target analyte.
In disclosed embodiments, the sensing device exhibits a change in
current, resistivity and/or voltage upon exposure to a target
analyte in the presence of UV light and/or visible light, with the
magnitude of such change dependent on the configuration of the
device. The architecture may provide for a single sensor, dual
sensors or multiple sensors on a single chip (e.g., comprising
nano-, micro-, or millimeter size wide-band gap oxide
semiconductors) which are functionalized with metal oxide and/or
metal nanoparticles and/or with their alloys. The architecture is
thus capable of simultaneously detecting one, two, or multiple
(e.g., 8 or more) analytes independently. The target analyte(s)
interacts with the functionalized material in the presence of
various carrier gases (e.g., air, oxygen, nitrogen, argon) that
results in a change in current, resistance and/or voltage in the
semiconductor backbone. For comparison, a chip consisting of a
non-functionalized, passivated element mimicking the design
architecture of the sensor element which is buried under an oxide
acts as a baseline, and does not respond to any of the target
analytes.
The semiconductor backbone may comprise etched/patterned ultra-thin
nano-clustered metal oxide, e.g. comprised of zinc oxide (ZnO),
titanium dioxide (TiO.sub.2), tin oxide (SnO.sub.2), nickel oxide
(NiO), copper oxide, cobalt oxide, iron oxide, zinc magnesium
oxide, magnesium oxide, vanadium oxide, lanthanum oxide, and/or
zirconium oxide. The second metal oxide functionalization consists
of another metal oxide, e.g. comprised of zinc oxide (ZnO),
titanium dioxide (TiO.sub.2), tin oxide (SnO.sub.2), nickel oxide
(NiO), copper oxide, cobalt oxide, iron oxide, zinc magnesium
oxide, magnesium oxide, vanadium oxide, lanthanum oxide, and/or
zirconium oxide.
Third metal nanoparticles may also be provided, e.g. comprised of
lithium, sodium, potassium, rubidium, cesium, francium, beryllium,
magnesium, calcium, strontium, barium, radium, aluminum, gallium,
indium, tin, thallium, lead, bismuth, scandium, titanium, vanadium,
chromium, manganese, iron, cobalt, nickel, copper, zinc, yttrium,
zirconium, niobium, molybdenum, technetium, ruthenium, rhodium,
palladium, silver, cadmium, lanthanum, hafnium, tantalum, tungsten,
rhenium, osmium, iridium, platinum, gold, mercury, and combinations
and alloys thereof.
In some implementations, the nanoparticle clusters are
multicomponent clusters comprising first metal-oxide nanoparticles
and second metal nanoparticles. The nanostructure has a first
bandgap, and the nanoparticle clusters have a second bandgap equal
to or less than said first bandgap. In disclosed embodiments, the
devices exhibit increased conductivity upon exposure to the target
analyte in the presence of radiation, including UV light and/or
visible light.
BRIEF DESCRIPTION OF THE DRAWINGS
The patent or application file contains at least one
drawing/photograph executed in color. Copies of this patent or
patent application publication with color drawing(s) will be
provided by the Office upon request and payment of the necessary
fee.
FIG. 1, plates (a) and (b), are schematic representations of a GaN
(Nanowire)-TiO.sub.2 (Nanocluster) hybrid sensor according to the
present invention. FIG. 1, plate (a) shows the sensor in the dark
showing surface depletion of the GaN nanowire, and FIG. 1, plate
(b) shows the sensor under UV excitation with photodesorption of
O.sub.2 due to hole capture.
FIG. 2, plate (a), illustrates graphically the photoresponse of a
hybrid device (diameter 300 nm) to 1000 ppm of benzene and toluene
mixed in air and nitrogen. FIG. 2, plate (b) illustrates the
response of a hybrid device (diameter 500 nm) to different
concentrations of water in air.
FIG. 3 is a schematic representation of depletion in the TiO.sub.2
NC in the presence of oxygen and water, and its effect on the
photogenerated charge carrier separation in GaN NW. Circles in
valence band indicate holes and circles in conduction band indicate
electrons.
FIG. 4 illustrates graphically the photo-response of the
GaN/(TiO.sub.2--Pt) device to 1000 .mu.mol/mol of ethanol in air
and nitrogen, and to 1000 .mu.mol/mol of water in air. The devices
did not respond to water in nitrogen. The air-gas mixture was
turned on at 0 s and turned off at 100 s.
FIG. 5, plate (a) illustrates graphically UV photo-response of the
GaN/(TiO.sub.2--Pt) hybrid device to 1000 .mu.mol/mol (ppm) of
methanol, ethanol, and water in air, and hydrogen in nitrogen. The
air-gas mixture was turned on at 0 s and turned off at 100 s. FIG.
5, plate (b) illustrates the cyclic response of the
GaN/(TiO.sub.2--Pt) hybrid device when exposed to 2500 .mu.mol/mol
(ppm) of hydrogen in nitrogen. The bias voltage for all the devices
was 5 V.
FIG. 6, plate (a) is a scanning electron microscope (SEM) image of
the NW bridge structure according to the present invention. FIG. 6,
plate (b) shows ZnO nanoparticles on the facets of GaN NW. FIG. 6,
plate (c) illustrates graphically current-voltage (I-V)
characteristics of the device before and after rapid thermal anneal
(RTA). FIG. 6, plate (d) is an x-ray diffraction (XRD)
.OMEGA.-2.THETA. scan of a 300-nm-thick ZnO film.
FIG. 7 illustrates graphically device response to 500-.mu.mol/mol
(ppm) of methanol. The inset graph at the bottom left shows the
sensitivity of two devices toward 500 .mu.mol/mol (ppm) of each
isomer of butanol (with Device 1 shown as the right bar above each
isomer, and Device 2 shown as the left bar above each isomer). The
inset graph at the bottom right shows the response to ethanol,
acetone, benzene, and hexane. Sensitivity (S) is given by
(I.sub.g-I.sub.a).times.100/I.sub.a, where I.sub.g is the device
current in the presence of an analyte in breathing air and I.sub.a
is the current in pure breathing air, both measured 300 s after the
flow is turned on. Percentage standard deviation of the device
sensitivity is 3.2% based on the five data points collected over a
period of 3 days in response to the breathing air.
FIG. 8 illustrates graphically device response to different flow
rates of breathing air (plate (a)) and nitrogen gas (plate (b)).
The flow rates of the gas are denoted as a=20 sccm, b=40 sccm, c=60
sccm, d=80 sccm, and e=100 sccm.
FIG. 9, plate (a) is a schematic illustration of a nanostructured
semiconductor-nanocluster hybrid gas sensor according to an
embodiment of the present invention. The sensor works with
low-intensity light from an LED. The emission wavelength is
determined by the semiconductor and metal-oxide bandgaps. FIG. 9,
plate (b) illustrates schematically an exemplary thin-film device
including a semiconductor backbone functionalized with TiO.sub.2 on
a sapphire substrate. The smoothness of the substrate and film
after thermal processing is shown in FIG. 9, plates (c) and
(d).
FIG. 10 is a schematic illustration of the mechanism of sensing
using the disclosed nanocluster-functionalized semiconductor
devices. The sensing is due to the effective separation of
photogenerated charge carriers in the semiconductor backbone caused
by surface potential modification of the backbone by the
nanocluster upon adsorption of chemicals. The light produces
electron-hole pairs in the semiconductor, and also surface defects
on the cluster due to photo desorption of oxygen and water.
FIG. 11 illustrates schematically the epitaxial layer structure
utilized in sensor device fabrication according to an embodiment of
the invention.
FIG. 12 illustrates schematically sensor designs according to the
present invention, including a sensor having serial architecture
(plate (a)), and a sensor having parallel architecture (plate
(b)).
FIG. 13 are schematic illustrations of a series architecture design
of a sensor with four segments, including a top view (plate (a))
and a cross-section view taken along the dashed line (plate (b)).
The sensor output is the voltage between the +V.sub.sensor and
ground pads. The V.sub.cal are the real-time calibration probes for
baseline and temperature drift compensating.
FIG. 14 illustrates graphically a generic sensor calibration curve.
Sensitivity S is defined as the slope of the sensor output response
vs. analyte concentration plot. The sensor output may be a change
in current, voltage, or resistance.
FIG. 15 is a schematic illustration of photoexcitation of both the
metal-oxide cluster and the GaN backbone using 365 nm light.
FIG. 16 is a schematic illustration showing selectivity tuning
using a multicomponent design of nanoclusters. As shown, the target
analyte is NO.sub.2 and the interfering chemical is CO.sub.2.
FIG. 17 illustrates graphically depletion depth induced by Pt
nanoclusters on GaN and TiO.sub.2 (as calculated by Equation (12)
below).
FIG. 18 is a schematic illustration of an integration scheme for
standalone system, showing components at roughly their actual
size.
FIG. 19 is a schematic illustration of a hybrid sensor fabrication
process according to the present invention.
FIG. 20, plates (a-c), are field-emission scanning electron
microscopy (FESEM) images of three different sputtered thickness of
TiO.sub.2 coatings: including 2 nm (plate (a)), 5 nm (plate (b)),
and 8 nm (plate (c)) of TiO.sub.2 sputtered on GaN nanowires.
FIG. 21 illustrates graphically an XRD .OMEGA.-2.THETA. scan of 150
nm thick TiO.sub.2 film deposited on SiO.sub.2/Si substrate at
300.degree. C. and annealed at 650.degree. C. for 45 s in RTA. All
indices correspond to the anatase phase [PDF#84-1285].
FIG. 22 illustrates typical morphologies of a 20 nm thick TiO.sub.2
film sputtered on n-GaN nanowires and annealed at 700.degree. C.
for 30 s. FIG. 22, plate (a) is a TEM image showing non-uniformly
distributed 2 nm to 10 nm diameter individual TiO.sub.2 particles,
with some of the particles marked by white circles. FIG. 22, plate
(b) is a high-resolution transmission electron microscopy (HRTEM)
image of an edge of the GaN nanowire with the sputtered TiO.sub.2
film. The FFT pattern from the boxed area is shown in exploded view
in the upper left inset, indicating 0.35 nm lattice fringes which
are consistent with a (101) reflecting plane of anatase.
FIG. 23, plate (a) is a BF-STEM image with 5 nm to 10 nm TiO.sub.2
nanoparticles barely visible near an edge of a GaN nanowire, with
some of the nanoparticles marked by circles. FIG. 23, plate (b) is
an ADF-STEM image of a TiO.sub.2-containing aggregate on the edge
of a GaN nanowire. FIG. 23, plate (c) is an X-ray spectrum of an
individual 5 nm TiO.sub.2 particle shown by circled portion `A` in
plate (a). FIG. 23, plate (d) is an EEL spectra recorded on
position 1 (tip of the aggregate) and position 2 (edge of the GaN
nanowire), as identified in plate (b), respectively.
FIG. 24 illustrates I-V characteristics of a GaN NW two-terminal
device in the dark at different stages of processing. The inset
shows the nanowire device with length 5.35 .mu.m and diameter 380
nm. The scale bar is 4 .mu.m. The thickness of sputtered TiO.sub.2
film was 8 nm.
FIG. 25, plate (a) illustrates graphically the dynamic photocurrent
of a bare GaN NW. FIG. 25, plate (b) illustrates the dynamic
photocurrent of a TiO.sub.2 coated (8 nm deposit) GaN NW. The
diameters of both nanowires were about 200 nm. The applied bias is
5 V in both cases.
FIG. 26 illustrates graphically the dynamic response of a single
GaN--TiO.sub.2 hybrid device to 1000 ppm of toluene. For each
cycle, the gas exposure time was 100 s. The inset shows the
nanowire device with 8.0 .mu.m length and diameter 500 nm. The
scale bar is 5 .mu.m.
FIG. 27, plate (a) illustrates the response of a single
nanowire-nanocluster hybrid sensor (inset shows nanowire with
diameter 500 nm) to 1000 ppm benzene, toluene, ethylbenzene,
chlorobenzene, and xylene in presence of UV excitation. FIG. 27,
plate (b) illustrates the response of a different sensor (inset
shows nanowire with diameter 300 nm) to 200 ppb toluene, benzene,
ethylbenzene, and xylene with UV excitation. The total flow in to
the chamber was kept constant at 20 sccm. The response to air is
also shown. The scale bars are 5 .mu.m.
FIG. 28 illustrates graphically a hybrid sensor's photoresponse
characteristics: FIG. 28, plate (a) shows the characteristics of
the device shown in FIG. 27, plate (a) for 100 to 10000 ppm
concentration range of toluene; FIG. 28, plate (b) shows the
characteristics of the device shown in FIG. 27, plate (b) for 50
ppb to 1 ppm concentration range of toluene.
FIG. 29 illustrates sensitivity plots of a GaN--TiO.sub.2
nanowire-nanocluster hybrid device (diameter 300 nm) for benzene,
toluene, ethylbenzene, chlorobenzene, and xylene. The plot
identifies the sensor's ability to measure wide range of
concentration of the indicated chemicals.
FIG. 30 is an HRTEM image of a GaN NW with TiO.sub.2 sputtered on
them, with plate (a) showing the GaN NW before Pt and plate (b)
showing after Pt deposition. Circled areas in plate (a) indicate
partially aggregated polycrystalline TiO.sub.2 particles on the NW
surface and on the supporting carbon film. Arrows in plate (b) in
the inset at the upper left mark Pt clusters decorating a 6 nm
diameter particle of titanium. The TiO.sub.2 particle exhibits 0.35
nm fringes corresponding to (101) lattice spacing of anatase
polymorph. 2 nm to 5 nm thick amorphized surface film are indicated
by black arrows.
FIG. 31 illustrate an HAADF-STEM of a GaN NW coated with TiO.sub.2
and Pt, with plate (a) showing 1 nm to 5 nm bright Pt nanoparticles
(shown by arrows) decorating surfaces of a polycrystalline
TiO.sub.2 island-like film and of a GaN nanowire. Medium grey
aggregated TiO.sub.2 particles (outlined by dashed line in plate
(a)) are barely visible on a thin carbon support near the edge of
the nanowire. Plate (b) is a high magnification image of the
supporting film near the edge of the nanowire exhibiting 0.23 nm to
0.25 nm (111) and 0.20 nm to 0.22 nm (200) fcc lattice fringes
belonging to Pt nanocrystallites, with arrows indicating
amorphous-like Pt clusters of 1 nm and less in diameter.
FIG. 32 illustrates I-V characteristics of the hybrid sensor device
at different stages of processing. FIG. 32, plate (a) shows
GaN/(TiO.sub.2--Pt) hybrids; FIG. 32, plate (b) shows GaN/Pt
hybrids. The inset image in plate (b) shows the plan-view SEM image
of a typical GaN NWNC hybrid sensor. The scale bar in the inset is
4 .mu.m.
FIG. 33 illustrates graphically depletion depth induced by Pt NCs
on GaN and TiO.sub.2 as calculated by equation 12.
FIG. 34 illustrates comparative sensing behavior of the three
hybrids for 1000 .mu.mol/mol (ppm) of analyte in air: light gray
bar graphs (benzene, toluene, ethylbenzene, xylene, chlorobenzene)
represent GaN/TiO.sub.2 hybrids, patterned bar graphs (ethanol,
methanol, and hydrogen) represent GaN/(TiO.sub.2--Pt) hybrids, and
white bar graph (hydrogen) represents GaN/Pt hybrids. Other
chemicals which did not produce any response in any one of the
hybrids are not included in the plot. The zero line is the baseline
response to 20 sccm of air and N.sub.2. For this plot the magnitude
of the sensitivity is used. The error bars represent the standard
deviation of the mean sensitivity values for every chemical
computed for 5 devices with diameters in the range of 200 nm-300
nm.
FIG. 35, plate (a) illustrates graphically the photo-response of
GaN/(TiO.sub.2--Pt) hybrid device to different concentrations of
methanol in air. FIG. 35, plate (b) shows photo-response of the
same device to different concentrations of hydrogen in nitrogen.
The air-gas mixture was turned on at 0 s and turned off at 100
s.
FIG. 36, plate (a) is a sensitivity plot of the GaN/(TiO.sub.2--Pt)
hybrid device to ethanol, methanol, and water in air and to
hydrogen in nitrogen ambient. FIG. 36, plate (b) shows graphically
a comparison of the sensitivity of GaN/(TiO.sub.2--Pt) and GaN/Pt
devices to different concentrations of hydrogen in nitrogen.
FIG. 37 illustrates schematically an exemplary fabrication flow
chart for semiconductor-nanocluster based gas sensors according to
the present invention.
FIG. 38, plate (a) is an image of large area etched nanostructures
of GaN on silicon and sapphire substrate formed according to
disclosed processes such as shown in FIG. 37. FIG. 38, plate (b)
shows an image of a nanostructure of GaN on silicon and sapphire
using ICP etching and post-etching surface treatment. This
nanostructure forms the backbone of the disclosed sensors in
disclosed embodiments.
FIG. 39 is an RTEM image of a GaN NW with TiO.sub.2 sputtered on
them. Circled portions indicate partially aggregated
polycrystalline TiO.sub.2 particles on the NW surface and on the
supporting carbon film.
FIG. 40 illustrates graphically I-V characteristics of a GaN NW
two-terminal device at different stages of processing.
FIG. 41, plate (a) illustrates graphically response of a single,
nanowire-nanocluster hybrid sensor to 100 ppb of benzene, toluene,
nitrobenzene, nitrotoluene, dinitrobenzene, dinitrotoluene and
trinitrotoluene in the presence of UV excitation. FIG. 41, plate
(b) shows the response of the device to different concentrations of
trinitrotoluene.
FIG. 42 is a sensitivity plot of a GaN--TiO.sub.2
nanowire-nanocluster hybrid device for benzene, toluene,
nitrotoluene, nitrobenzene, DNT, DNB and TNT.
FIG. 43 illustrates sensitivity of two different
nanowire-nanocluster hybrid sensors to 100 ppb of the different
aromatic compounds.
FIG. 44, plate (a), illustrates the dynamic responses of a
TiO.sub.2 based sensor exposed to 250 ppm NO.sub.2 mixed with
breathing air under UV illumination and dark at room temperature.
Plate (b) illustrates the response under UV at mixture of 100 ppm,
250 ppm, and 500 ppm with breathing air. The inset in plate (b)
shows the measured responses under UV as a function of NO.sub.2
concentrations with uncertainty. Sensitivity S is presented by
(I.sub.g-I.sub.a).times.100/I.sub.a, wherein I.sub.g is the device
current in the presence of an analyte in breathing air and Ia is
the current in pure breathing air, both measured 300 s after the
flow is turned on.
FIG. 45 illustrates schematically an NO.sub.2 gas sensing mechanism
of the TiO.sub.2 sensor under UV illumination: plate (a) shows the
mechanism in a dark environment with breathing air in; plate (b)
shows the mechanism under UV illumination in breathing air; and
plate (c) shows the mechanism under UV illumination with mixture of
NO.sub.2 and breathing air (all at room temperature).
FIG. 46 illustrates graphically the dynamic response of the
TiO.sub.2 based sensor exposed to 500 ppm NO.sub.2 under UV
illumination and under dark at room temperature.
FIG. 47, plate (a) illustrates a GIXRD scan of thermally processed
ultrathin TiO.sub.2 film, and plate (b) illustrates optical
properties (bandgap).
FIG. 48, plate (a) illustrates schematically a SnO.sub.2--Cu
nanocluster CO.sub.2 sensor. Plates (b) and (c) are AFM images of
the SnO.sub.2--Cu nanocluster CO.sub.2 sensor.
FIG. 49 illustrates the dynamic responses of the SnO.sub.2--Cu
based sensor exposed to CO.sub.2 at room temperature at
concentrations of 1000 ppm and 5000 ppm. For each cycle, the gas
exposure time was 300 s.
FIG. 50 illustrates graphically the response of the SnO.sub.2 based
sensor at different relative humidity (RH) concentrations at room
temperature.
FIG. 51, plate (a) illustrates the dynamic response of a TiO.sub.2
based sensor exposed to methanol at room temperature and at a
concentration of 500 ppm. Plate (b) illustrates the dynamic
response of a ZnO based sensor exposed to benzene at room
temperature and a concentration of 500 ppm. Plate (c) illustrates
the dynamic response of the ZnO based sensor exposed to hexane at
room temperature and a concentration of 100 ppm.
FIG. 52 illustrates graphically the dynamic responses of a
ZnO--Pd--Ag based sensor exposed to H.sub.2 at room
temperature.
FIG. 53 illustrates schematically an exemplary layout of on chip
elements of a sensor device in accordance with the present
invention.
FIG. 54 illustrates schematically a micro-heater embedded into a
sensor device in accordance with disclosed embodiments of the
present invention.
FIG. 55 illustrates the temperature profile of 50 .mu.m microheater
made from a Ti/Ni metal stack MH recorded at 5 V bias voltage
(plate (a)) and 10 V bias voltage (plate (b)).
FIG. 56 illustrates graphically the dynamic response of a
functionalized GaN sensor device for sensing H.sub.2S
(concentration 50 ppm) in dry air.
FIG. 57 illustrates graphically the dynamic response of a
functionalized GaN sensor device for sensing NO.sub.2
(concentration 500 ppm) in dry air (22.degree. C., relative
humidity 0-5%).
FIG. 58 illustrates graphically the dynamic response of a
functionalized GaN sensor device for sensing SO.sub.2
(concentration 10 ppm) in dry air (22.degree. C., relative humidity
0-5%).
FIG. 59 illustrates graphically the dynamic response of a
functionalized GaN sensor device for sensing CO.sub.2
(concentration 5000 ppm) in dry air (22.degree. C., relative
humidity 0-5%).
FIG. 60 illustrates an exemplary sensor module in accordance with
the present invention.
DETAILED DESCRIPTION OF THE INVENTION
The present invention is directed to sensor devices including a
semiconductor nanostructure, such as a micro or nanodevice, or
nanowire (NW), having a surface functionalized or decorated with
metal or metal-oxide nanoparticles or nanoclusters. When
metal/metal-oxide nanoparticles selected according to the disclosed
methods are placed on the surface of a nanostructure, significant
changes result in the physical properties of the system. The
nanoparticles increase the adsorption of chemical species by
introducing additional adsorption sites, thereby increasing the
sensitivity of the resulting system.
The metal or metal-oxide nanoparticles may be selected to act as
catalysts designed to lower the activation energy of a specific
reaction, which produces active radicals by dissociating the
adsorbed species. These radicals can then spill-over to a
semiconductor structure (see Sermon P A and Bond G C (19703)
"Hydrogen Spillover," Catal. Rev. 8(2):211-239; Conner W C et al.
(1986) "Spillover of sorbed species," Adv. Catal. 34:1), where they
are more effective in charge carrier transfer. Further, the
selected nanoparticles modulate the current through the nanowire
through formation of nanosized depletion regions, which is in turn
a function of the adsorption on the nanoparticles. Nanoparticles or
nanoclusters suitable for the present invention include virtually
any metal-oxide and/or metal. Thus, it should be understood that
the present invention is not limited to the particular exemplary
metal-oxides and/or metals disclosed in the various embodiments and
examples herein.
According to one embodiment, nanowire-nanocluster hybrid chemical
sensors were realized by functionalizing n-type (Si doped) gallium
nitride (GaN) NWs with TiO.sub.2 nanoclusters. The sensors
selectively sense benzene and related aromatic environmental
pollutants, such as toluene, ethylbenzene, and xylene (sometimes
referred to as BTEX). GaN is a wide-bandgap semiconductor (3.4 eV),
with unique properties (Morkoc H (1999) Nitride Semiconductors and
Devices, Springer series in Materials Science, Vol. 32, Springer,
Berlin). Its chemical inertness and capability of operating in
extreme environments (high-temperatures, presence of radiation,
extreme pH levels) is thus suitable for the disclosed sensor
design. TiO.sub.2 is a photocatalytic semiconductor with a bandgap
energy of 3.2 eV (anatase phase). Photocatalytic oxidation of
various organic contaminants over titanium dioxide (TiO.sub.2) has
been previously studied (see Mills A and Hunte S L (1997) "An
overview of of semiconductor photocatalysis," J. Photochem.
Photobiol. A 108:1-35; Luo Y and Ollis D F (1996) "Heterogeneous
photocatalytic oxidation of trichloroethylene and toluene mixtures
in air: Kinetic promotion and inhibition, time-dependent catalyst
activity," J. Catal. 163:1-11). The TiO.sub.2 nanoclusters were
thus selected to act as nanocatalysts to increase the sensitivity,
lower the detection time, and enable the selectivity of the
structures to be tailored to organic analytes.
The hybrid sensor devices may be developed by fabricating
two-terminal devices using individual GaN NWs followed by the
deposition of TiO.sub.2 nanoclusters using radio frequency (RF)
magnetron sputtering. The sensor fabrication process employed
standard micro-fabrication techniques. X-ray diffraction (XRD) and
high-resolution analytical transmission electron microscopy using
energy-dispersive X-ray and electron energy-loss spectroscopies
confirmed the presence of anatase phase in TiO.sub.2 clusters after
post-deposition anneal at 700.degree. C.
A change of current was observed for these hybrid sensors when
exposed to the vapors of aromatic compounds (e.g., benzene,
toluene, ethylbenzene, xylene, and chlorobenzene mixed with air)
under UV excitation, while they had minimal or no response to
non-aromatic organic compounds such as methanol, ethanol,
isopropanol, chloroform, acetone, and 1, 3-hexadiene. The
sensitivity range for the noted aromatic compounds, except
chlorobenzene, were from about 1% down to about 50 parts per
billion (ppb) at room-temperature. By combining the enhanced
catalytic properties of the TiO.sub.2 nanoclusters with the
sensitive transduction capability of the nanowires, an
ultra-sensitive and selective chemical sensing architecture is
achieved.
As discussed in further detail in Example 1 below, GaN--TiO.sub.2
(nanowire-nanocluster) hybrid sensors demonstrated a response to
specific volatile organic compounds mixed with air at ambient
temperature and humidity. In the presence of UV light (e.g., having
a wavelength in the range of about 10 nm to about 400 nm), these
hybrid sensor devices exhibited change in the photocurrent when
exposed to benzene, toluene, ethylbenzene, xylene, and
chlorobenzene mixed in air. However, gases like methanol, ethanol,
isopropanol, chloroform, acetone, and 1, 3-hexadiene exhibited
little or no change in the electrical characteristics of the
devices, thus demonstrating the selective response of these sensors
to the aromatic compounds. Benzene, toluene, ethylbenzene, and
xylene were detected by the disclosed sensors at a concentration
level as low as 50 ppb in air. In addition, the disclosed sensor
devices are highly stable and able to sense aromatic compounds in
air reliably for a wide range of concentrations (e.g., 50 ppb to
1%).
In addition, the disclosed sensors demonstrated highly sensitive
and selective detection of traces of nitro-aromatic explosive
compounds. As discussed in further detail in Example 5 below,
GaN/TiO.sub.2 nanowire-nanocluster hybrid sensors detected
different aromatic and nitroaromatic compounds at room temperature.
For example, the GaN/TiO.sub.2 hybrids were able to detect
trinitrotoluene (TNT) concentrations as low as 500 pmol/mol (ppt)
in air and dinitrobenzene concentrations as low as 10 nmol/mol
(ppb) in air in approximately 30 seconds. The noted sensitivity
range of the devices for TNT was from 8 ppm down to as low as 500
ppt. The detection limit of dinitrotoluene, nitrobenzene,
nitrotoluene, toluene and benzene in air is about 100 ppb with a
response time of .apprxeq.75 seconds. Devices according to the
present invention exhibited sensitive and selective response to TNT
when compared to interfering compounds like toluene. Thus, the
disclosed sensors are suitable for use as highly sensitive,
selective, low-power and smart explosive detectors, which are
relatively inexpensive to manufacture in larger quantities.
Based on structural analysis, an exemplary mechanism that
qualitatively explains the hybrid sensor's response to different
analytes is shown in FIG. 1. With regard to the photocatalytic
processes on the TiO.sub.2 surface, the oxygen vacancy defects
(Ti.sup.3+ sites) on the surface of TiO.sub.2 are the active sites
responsible for adsorption of species like oxygen, water, and
organic molecules (see Yates Jr J T (2009) "Photochemistry on
TiO.sub.2: mechanisms behind the surface chemistry," Surf. Sci.
603:1605-1612). Interestingly, a relatively defect free TiO.sub.2
surface, generated by annealing in high-oxygen flux, is chemically
inactive (Li M et al. (1999) "Oxygen-induced restructuring of
rutile TiO.sub.2(110): formation mechanism, atomic models, and
influence on surface chemistry," Faraday Discuss. 114:245).
Experimental studies and simulations reveal that molecular oxygen
is chemisorbed on the surface vacancies (Ti.sup.3+ sites),
acquiring a negative charge as shown in FIG. 1, plate (a) (Anpo M
et al. (1999) "Generation of superoxide ions at oxide surfaces,"
Top. Catal. 8:189-198; de Lara-Castells M P and Krause J L (2003)
"Theoretical study of the UV-induced desorption of molecular oxygen
from the reduced TiO.sub.2 (110) surface," J. Chem. Phys.
118:5098). This is due to the presence of the localized electron
density at or near exposed Ti.sup.3+ atoms on the TiO.sub.2 surface
(Henderson M A et al. (1999) "Interaction of Molecular Oxygen with
the Vacuum-Annealed TiO.sub.2(110) Surface: Molecular and
Dissociative Channels," J. Phys. Chem. B 103:5328-5337). Water may
also be present on the TiO.sub.2 cluster surface via molecular or
dissociative adsorption, producing OH.sup.- species on the defect
sites (Lee F K et al. (2007) "Role of water adsorption in
photoinduced superhydrophilicity on TiO.sub.2 thin films," Appl.
Phys. Lett. 90:181928; Bikondoa O et al. (2006) "Direct
visualization of defect-mediated dissociation of water on TiO.sub.2
(110)," Nat. Mater. 5:189-192).
Although most of the theoretical and experimental studies on oxygen
and water adsorption are done for the (110) surface of rutile
phase, there are studies that suggest that similar adsorption
behavior is also expected for the anatase surface (Wahab H S et al.
(2008) "Computational investigation of water and oxygen adsorption
on the anatase TiO.sub.2 (100) surface," J. Mol. Chem. Struct.
868:101-108). The GaN NW has a surface depletion region as shown in
FIG. 1, plate (a), which determines its dark conductivity (Sanford
N A et al. (2010) "Steady-state and transient photoconductivity in
c-axis GaN nanowires grown by nitrogen-plasma-assisted molecular
beam epitaxy," J. Appl. Phy. 107:034318).
In the presence of UV excitation with an energy above the bandgap
energy of anatase TiO.sub.2 (3.2 eV) and GaN (3.4 eV),
electron-hole pairs are generated both in the GaN NW and in the
TiO.sub.2 cluster, as shown in FIG. 1, plate (b). Photogenerated
holes in the nanowire tend to diffuse towards the surface due to
the surface band bending. This effect of separation of
photogenerated charge carriers results in a longer lifetime of
photogenerated electrons, which in turn enhances the photoresponse
of the nanowire devices. On the TiO.sub.2 cluster surface, however,
the photogenerated charge carriers lead to a different phenomenon.
In n-type semiconductor oxides such as TiO.sub.2, the surface
adsorption produces upward band-bending, which drives the
photogenerated holes towards the surface. The chemisorbed oxygen
molecule (O.sub.2.sup.-) and hydroxide ions (OH.sup.-) can readily
capture a hole and desorb as shown in FIG. 1, plate (b) (Perkins C
L and Henderson M A (2001) "Photodesorption and Trapping of
Molecular Oxygen at the TiO.sub.2(110)--Water Ice Interface," J.
Phys. Chem. B. 105:3856-3863; Thompson T L and Yates J T Jr. (2006)
"Control of a surface photochemical process by fractal electron
transport across the surface: O(2) photodesorption from TiO
(2)(110)," J. Phys. Chem. B 110:7431-7435). The decrease of
photocurrent through these hybrid sensors when exposed to 20 sscm
of air may be due to the increase in oxygen concentration at the
surface of TiO.sub.2 clusters, leading to an increase in trapping
of photogenerated holes at the surface. This process results in
increased lifetime of photogenerated electrons. As these nanowires
are n-type, excess negative charge on the surface of the wire (on
the TiO.sub.2 clusters) reduces the nanowire current, thus
providing a local-gating effect due to net negative charge
accumulation in the TiO.sub.2 clusters. Thus, the photoinduced
oxygen desorption and subsequent capture of holes by organic
adsorbate molecules on the surface of TiO.sub.2 clusters produces
the local-gating effect, which is responsible for the sensing
action of the disclosed sensor devices. The adsorbed hydroxyl ions
may also trap a hole forming OH.sup.- species. Other effects such
as diffusion of carriers between the clusters and the nanowire may
also have a role in the sensing properties of the sensors.
Although some embodiments are described in term of excitation in
the presence of UV light, it should be understood that excitation
by radiation of other wavelengths may be more suitable for devices
having other types of metal-oxide and/or metal nanoparticles. For
example, excitation in the presence of visible light (i.e., having
a wavelength of between about 380 nm and about 740 nm) is suitable
for some embodiments.
The process noted above and shown in FIG. 1 also explains sensor
response when exposed to N.sub.2 flow, as shown in FIG. 2, plate
(a). In the presence of 20 sccm of N.sub.2 flow, the photocurrent
in the sensors increases significantly in comparison with 20 sccm
of air flow. In an N.sub.2 environment, oxygen is desorbed from the
surface vacancy sites by capturing photogenerated holes, but does
not get re-adsorbed, resulting in significant reduction of hole
capture. As such, the photogenerated electron-hole pairs recombine
effectively in the cluster. Thus, the photocurrent through the
nanowire/nanocluster hybrid sensor, which is otherwise increased
due to the local-gating effect by the TiO.sub.2 clusters, is absent
in an N.sub.2 environment.
In the presence of water in air, the photocurrent through these
sensors recovers towards the level without air flow, as seen in
FIG. 2, plate (b), indicating a reduction of the hole trapping due
to adsorption of water on the TiO.sub.2 surface. Water may be
adsorbed as a molecule on the defect sites replacing O.sub.2 (see
Herman G S et al. (2003) "Experimental Investigation of the
Interaction of Water and Methanol with Anatase-TiO.sub.2(101)," J.
Phys. Chem. B 107:2788-2795). With increasing water concentration,
more defects are filled with water. If the adsorbed water
dissociates and produces OH.sup.- species, then it is possible that
it will act as hole traps and decrease the photocurrent the same
way the photodesorption of oxygen does. A competition between the
molecular water adsorption (reducing hole capture) and dissociative
water adsorption (increasing hole capture) is possible, with the
dominant process ultimately determining the photocurrent level in
the nanowires in the presence of water.
The presence of aromatic compounds such as benzene, ethylbenzene,
chlorobenzene, and xylene in air reduced the photocurrent (e.g. see
FIG. 2, plate (a)). Organic molecules are known hole-trapping
adsorbates (see Yamakata A et al. (2002) "Electron-and hole-capture
reactions on Pt/TiO.sub.2 photocatalyst exposed to methanol vapor
studied with time-resolved infrared absorption spectroscopy," J.
Phys. Chem. B 106:9122-9125). Most aromatic compounds show high
affinity for electrophilic aromatic substitution. The exact
mechanism of photooxidation of adsorbed organic compounds on
TiO.sub.2 is complex. However, it is believed that oxidation occurs
by either indirect oxidation via the surface-bound hydroxyl radical
(i.e., a trapped hole at the TiO.sub.2 surface) or directly via the
valence-band hole before it is trapped either within the particle
or at the particle surface (see Nosaka Y et al. (1998) "Factors
governing the initial process of TiO.sub.2 photocatalysis studied
by means of in situ electron spin resonance measurements," J. Phys.
Chem. B 102:10279-10283; Mao Y et al. (1991) "Identification of
organic acids and other intermediates in oxidative degradation of
chlorinated ethanes on titania surfaces en route to mineralization:
a combined photocatalytic and radiation chemical study," J. Phys.
Chem. 95:10080-10089). In the presence of air (with residual water)
hydroxyl mediated hole transfer to adsorbates such as benzene,
xylene is dominant, whereas in the N.sub.2 environment direct
transfer of valence band holes to aromatic adsorbates could be
possible.
Irrespective of the hole transfer mechanism, the presence of
additional hole traps reduces the sensor photocurrent, as observed
in the presence of benzene mixed with N.sub.2 and air as shown in
FIG. 2, plate (a). The model disclosed herein qualitatively
explains the observed trends for compounds tested, such as benzene,
ethylbenzene, chlorobenzene, and xylene. However, toluene exhibits
a different trend, which may be due to other second order effects
other than or in addition to the hole trapping mechanism.
The disclosed mechanism is further validated when comparing
ionization energies of various compounds tested with the responses
generated when the sensors are exposed to them (see Table I). The
effectiveness of the process of hole transfer to the adsorbed
organic molecules relates to the compound's ability to donate an
electron (i.e. the lower the ionization energy of a compound, the
easier for it to donate an electron or capture a hole). The
observed sensitivity trend for benzene (lowest sensitivity),
ethylbenzene, and xylene (highest sensitivity) correlates with
their ionization energies as shown in Table I, with benzene being
the highest and xylene the lowest among the three.
TABLE-US-00001 TABLE I Physical Properties of Various Compounds
Tested Organic Ionization Potential Compound Sensitivity (eV)
Chloroform No 11.37 Ethanol No 10.62 Isopropanol No 10.16
Cyclohexane Yes 9.98 Acetone No 9.69 Benzene Yes (Min) 9.25
Chlorobenzene Yes 9.07 Toluene Yes 8.82 Ethylbenzene Yes 8.77
Xylene Yes (Max) 8.52 1,3-Hexadiene No 8.50
As shown in Table I, the sensitivity trend is consistent for
aromatics, given 1,3-Hexadiene produced no response in the sensors.
Although most functional groups with either a non-bonded lone pair
or p-conjugation show oxidative reactivity towards TiO.sub.2
(Hoffman M R et al. (1995) "Environmental Applications of
Semiconductor Photocatalysis," Chem. Rev. 95:69-96), aromatic
compounds are more easily photocatalyzed than aliphatic ones under
the same conditions (Carp O et al. (2004) "Photoinduced reactivity
of titanium dioxide," Prog. Solid St. Chem. 32:33-177).
Thus, the metal-oxide nanoclusters (TiO.sub.2) on GaN NWs or
nanostructures demonstrate the disclosed architecture for highly
selective gas sensing. The exemplary sensors are capable of
selectively sensing benzene and related aromatic compounds at
nmol/mol (ppb) level in air at room-temperature under UV
excitation.
According to another embodiment, the specific selectivity of the
disclosed nanowire (or nanostructure)/nanocluster hybrid sensors
may be tailored using a multi-component nanocluster design. For
example, catalytic metals (e.g., platinum (Pt), palladium (Pd),
and/or any other transition metals) are deposited onto the surface
of oxide photocatalysts in order to enhance their catalytic
activity. Metal clusters on a metal-oxide catalyst alter the
behavior of the metal-oxide catalyst by any one, or a combination
of, the following mechanisms: 1) changing the surface adsorption
behavior as metals often have very different heat of adsorption
values compared to the metal-oxides; 2) enabling catalytic
decomposition of certain analytes on the metal surface, which
otherwise would not be possible on the oxide surface; 3)
transporting active species to the metal-oxide support by the
spill-over effect from the metal cluster; 4) generating a higher
degree of interface states, thus increasing reactive surface area
reaction area; 5) changing the local electron properties of the
metal clusters, such as workfunction, due to adsorption of gases;
and 6) effectively separating photogenerated carriers in the
underlying metal-oxide. The effect of transition metal loading such
as iron (Fe), copper (Cu), Pt, Pd, and rhodium (Rh) onto TiO.sub.2
has been evaluated for photocatalytic decomposition of various
chemicals in both gas-solid and liquid-solid regimes.
In one implementation, the selectivity of the titanium dioxide
(TiO.sub.2) nanocluster-coated gallium nitride (GaN) nanostructure
sensor device is altered by addition of platinum (Pt) nanoclusters.
In another implementation, the sensor device includes Pt
nanocluster-coated GaN nanostructure. The hybrid sensor devices may
be developed by fabricating two-terminal devices using individual
GaN NWs or nanostructures followed by the deposition of TiO.sub.2
and/or Pt nanoclusters (NCs) using a sputtering technique, as
described above.
The sensing characteristics of GaN/(TiO.sub.2--Pt)
nanowire-nanocluster (NWNC) hybrids and GaN/(Pt) NWNC hybrids is
altered as compared to GaN/TiO.sub.2 sensors. The GaN/TiO.sub.2
NWNC hybrids show remarkable selectivity to benzene and related
aromatic compounds with no measureable response for other analytes,
as discussed above. However, the addition of Pt NCs to
GaN/TiO.sub.2 sensors dramatically alters the sensing behavior,
making them sensitive only to methanol, ethanol, and hydrogen, but
not to other chemicals tested, as discussed in further detail in
Example 2 below.
The GaN/(TiO.sub.2--Pt) hybrid sensors were able to detect ethanol
and methanol concentrations of 100 nmol/mol (ppb) in air in
approximately 100 seconds, and hydrogen concentrations from 1
.mu.mol/mol (ppm) to 1% in nitrogen in less than 60 seconds.
However, GaN/Pt hybrid sensors showed limited sensitivity only
towards hydrogen and not towards any alcohols. All the hybrid
sensors are operable at room temperature and are photomodulated
(i.e., responding to analytes only in the presence of light, e.g.,
ultra violet (UV) light). The selectivity achieved is significant
from the standpoint of numerous applications requiring
room-temperature sensing, such as hydrogen sensing and sensitive
alcohol monitoring. For example, the dynamic response of an
exemplary TiO.sub.2 based sensor exposed to methanol at room
temperature and at a concentration of 500 ppm is illustrated in
FIG. 51, plate (a). The disclosed sensors therefore demonstrate
tremendous potential for tailoring the selectivity of the hybrid
nanosensors for a multitude of environmental and industrial sensing
applications.
A qualitative understanding of the selective sensing mechanism of
the disclosed sensors may be developed by considering how different
molecules adsorb on the nanocluster surfaces, and determining the
roles of intermediate reactions in the sensitivity of the sensors.
While some of the embodiments, examples and explanation describe
the invention in terms of NWs, it should be understood that other
nanostructures or microstructures may be utilized. Accordingly, the
present invention is not limited to sensors including NWs.
The Photocurrent in GaN/(TiO.sub.2--Pt) Hybrid Sensors in the
Presence of Air, Nitrogen, and Water:
The oxygen vacancy defects (Ti.sup.3+ sites) on the surface of
TiO.sub.2 are the "active sites" for the adsorption of species like
oxygen, water, and organic molecules (Yates Jr J T (2009)
"Photochemistry on TiO.sub.2: mechanisms behind the surface
chemistry," Surf Sci. 603:1605-1612; Bikondoa O et al. (2006)
"Direct visualization of defect-mediated dissociation of water on
TiO.sub.2(110)," Nat. Mater. 5:189-192). It has been observed that
oxygen adsorption on photocatalyst powders such as TiO.sub.2 and
ZnO quenches the photoluminescence (PL) intensity, while adsorption
of water produces an enhancement of the PL. Electron-trapping
adsorbates, such as oxygen, increase the band-bending of TiO.sub.2,
which facilitates the separation of photogenerated electron hole
pairs in the oxide. Subsequently, the PL intensity is decreased as
the photogenerated charge carries cannot recombine efficiently.
Conversely, in the case of water, the band bending is reduced,
resulting in an increase in the PL intensity. In explaining the
observed behavior of the hybrid sensors, the depletion effect
induced by the TiO.sub.2 clusters on GaN NW is considered.
Considering an inverse relationship, i.e., increase in depletion of
the TiO.sub.2 cluster leads to a decrease in the depletion width in
the GaN NW and vice versa, some of the observed sensing behavior is
explained.
As shown in FIG. 3, when oxygen is adsorbed on the TiO.sub.2 NC
surface, the depletion width in the NC increases, leading to a
decrease in the depletion width in the NW. Adsorption of water,
nitrogen, and alcohol produce the reverse effect: they decrease the
depletion width of the TiO.sub.2 NC, leading to an increase in the
band-bending on the GaN NW. Increased band-bending in the GaN NW
results in an effective separation of charge carriers, leading to
an increase in photocurrent through the NW. This qualitatively
explains the increase in the photocurrent when the hybrid sensor is
exposed to water mixed with air or with pure nitrogen (see FIG. 4).
However, the increase in the photocurrent when exposed to 20 sccm
of air flow is not fully explained. Under air flow, more oxygen
should adsorb on the NCs, causing an increase in the depletion
width of the cluster. This should have resulted in a decrease in
the photocurrent based on our assumption; however, an increase in
the photocurrent is exhibited (FIG. 4) when 20 sccm of air is
passed through the chamber.
In the absence of UV light, the absorption or desorption of
chemicals from the cluster surfaces cannot modulate the dark
current through the nanowire. In the dark, the surface depletion
layer of the GaN NW is thicker compared to under UV excitation (see
Mansfield L M et al. (2009) "GaN nanowire carrier concentration
calculated from light and dark resistance measurements," Journal of
Electronic Materials 38:495-504). The minority carrier (hole)
concentration is also significantly lower. Thus the NCs are
ineffective in modulating the dark current through the NW.
Mechanism of Sensing of Alcohols and Hydrogen by
GaN/(TiO.sub.2--Pt) NWNC Sensors
Adsorption of alcohols (RCH.sub.2--OH) on the TiO.sub.2 surface
leads to their oxidation (Kim K S and Barteau M A (1989) "Reaction
of Methanol on TiO.sub.2," Surface Science 223:13-32). Although
there are various mechanisms of oxidation of adsorbed alcohols on
TiO.sub.2 surface, focus is on the oxidation of alcohols by
photogenerated holes. The process is described by the following
reactions:
RCH.sub.2--OH(g).revreaction.RCH.sub.2.revreaction.OH(ads)
(Equation 1) RCH.sub.2-OH(ads)+.sub.h.sup.+(photogenerated
hole).revreaction.RCH.sub.2--OH.sup.+(ads) (Equation 2)
RCH.sub.2--OH.sup.+(ads).revreaction.RCH--OH.sup..circle-solid.(ads)+H.su-
p.+(ads) (Equation 3)
RCH--OH.sup..circle-solid.(ads).revreaction.RCHO(ads)+H.sup.+(ads)+e.sup.-
- (Equation 4) where (ads) and (g) represent adsorbed and gas phase
species, respectively. For Equation 4 to proceed in the forward
directions, the H.sup.+ species should be removed effectively. It
is possible that from TiO.sub.2 NCs the H.sup.+ species can
spill-over on to Pt clusters nearby, where they can be reduced to
form H.sub.2: 2H.sup.+(ads)+2e.sup.-.revreaction.H.sub.2(g)
(Equation 5)
As H.sup.+ reduction and hydrogen-hydrogen recombination is weak on
the bare TiO.sub.2 surface (Fujishima A et al. (2008) "TiO.sub.2
photocatalysis and related surface phenomena," Surf Sci. Rep.
63:515-582), the rate of alcohol oxidation to aldehyde might be
affected by the H.sup.+ reduction and hydrogen-hydrogen
recombination on the Pt NCs. Adsorption of alcohols and their
subsequent oxidation due to trapping of photogenerated holes leads
to a decrease in the band bending of TiO.sub.2 NCs. As shown in
FIG. 3, this leads to an increase in the NW photocurrent, which is
observed for the GaN/(TiO.sub.2--Pt) sensors when exposed to
methanol and ethanol (FIG. 4). It is likely that the production of
H.sub.2 on Pt is the key for sensing alcohols by
GaN/(TiO.sub.2--Pt) sensors. Additionally, H.sub.2 on Pt surface
can dissociate and diffuse to the Pt/TiO.sub.2 interface. Atomic
hydrogen is shown to produce an interface dipole layer, which
reduces the effective work-function of Pt (Du X et al. (2002) "A
New Highly Selective H.sub.2 Sensor Based on TiO.sub.2/PtO--Pt
Dual-Layer Films," Chem. Mater. 14:3953-3957). Effective reduction
of Pt workfunction also reduces the depletion width in TiO.sub.2,
which according to the model in FIG. 4, also leads to an increase
in the photocurrent when these sensors are exposed to alcohols. In
the presence of hydrogen in nitrogen, the workfunction change of Pt
NCs due to hydrogen adsorption is the likely cause for the sensing
behavior of these sensor hybrids.
Selectivity of GaN/(TiO.sub.2--Pt), GaN/Pt, and GaN/TiO.sub.2NWNC
Hybrid Sensors
A significant finding of the present invention is the change in the
selectivity of GaN/TiO.sub.2 hybrid sensors due to the addition of
Pt NCs. The observed selectivity behavior of the three hybrids can
be qualitatively explained if the heat of adsorption of the
analytes on TiO.sub.2 and Pt surfaces is considered as shown in
Table II and their ionization energies presented in Table III.
TABLE-US-00002 TABLE II Heat of Adsorption for Methanol, Benzene,
and Hydrogen on Pt and TiO.sub.2 (Anatase*) Hydrogen Methanol
Benzene Surface (kJ/mol) (kJ/mol) (kJ/mol) TiO.sub.2 Negligible 92
64 Pt 100 48 117 *The heat of absorption values for TiO2 rutile
surfaces are comparable
TABLE-US-00003 TABLE III Ionization Energy of the Analytes (CRC
Handbook of Chemistry and Physics, 84th ed.; CRC Press: Boca Raton,
FL., 2003): Organic Ionization Energy Compound (eV) Methanol 10.85
Hydrogen 13.5 Benzene 9.25
Referring to Table II, benzene has a higher heat of adsorption on
Pt than on TiO.sub.2. Therefore, benzene will preferentially adsorb
on Pt in the TiO.sub.2--Pt cluster. Now, in the absence of Pt, when
the benzene is adsorbed on TiO.sub.2 it can interact with the
photogenerated charge carriers resulting in the sensing behavior of
GaN/TiO.sub.2 devices. However, if benzene is adsorbed on Pt (such
as in the case of TiO.sub.2--Pt and Pt nanoclusters on GaN) then
benzene molecules cannot interact with photogenerated charge
carriers in TiO.sub.2, and therefore are ineffective in producing
any current modulation in the nanowire. Thus, benzene is detected
by GaN/TiO.sub.2 sensor devices, but not by GaN/(TiO.sub.2--Pt) and
GaN/Pt sensor devices.
Further, methanol is detected by GaN/(TiO.sub.2--Pt) sensors only,
and not by GaN/TiO.sub.2 and GaN/Pt sensors. From Table III,
methanol (unlike benzene) effectively adsorbs on TiO.sub.2, whether
Pt is present or absent (as the heat of adsorption of methanol is
higher on TiO.sub.2 than Pt). It is believed that methanol on
TiO.sub.2 in the absence of Pt does not participate in
photogenerated carrier trapping as efficiently as benzene and other
aromatic compounds on the TiO.sub.2 nanoclusters. Referring to
Table III, the ionization energy of methanol, hydrogen, and benzene
is shown. The effectiveness of the process of hole transfer to the
adsorbed organic molecules is related to the compound's ability to
donate an electron (i.e. the lower the ionization energy of a
compound, the easier for it to donate an electron or capture a
hole). However, in the presence of Pt nanoclusters nearby, methanol
adsorption on TiO.sub.2 ultimately leads to formation of H.sup.+
through photo-oxidation of methanol, and eventually H.sub.2, which
is the key molecule for sensing of methanol by (TiO.sub.2--Pt) NCs
on GaN NW. A similar mechanism applies for ethanol sensing by the
GaN/(TiO.sub.2--Pt) hybrids.
Hydrogen is detected by GaN/(TiO.sub.2--Pt) and GaN/Pt hybrids, and
not by GaN/TiO.sub.2 NWNC sensors, and GaN/(TiO.sub.2--Pt) sensors
have a higher response to hydrogen than to alcohols. From Table II,
hydrogen has negligible heat of adsorption on TiO.sub.2, thus
GaN/TiO.sub.2 devices are not sensitive to hydrogen. However, in
the presence of Pt NCs on TiO.sub.2, hydrogen can adsorb on the Pt
NCs. Once adsorbed, hydrogen can modify the workfunction of Pt,
resulting in a change in the photocurrent through the nanowire.
However, this is not the only mechanism, as that would imply that
GaN/Pt hybrids should be equally sensitive to H.sub.2. It is
believed that when hydrogen is adsorbed on the TiO.sub.2--Pt NC, it
also reduces the TiO.sub.2 surface. Thus, in the presence of only
Pt on GaN, workfunction modification of Pt solely produces change
in the photocurrent in the NW. However, in the presence of Pt and
TiO.sub.2 NCs, hydrogen adsorption leads to the modulation of the
photocurrent in GaN NW, through modulation of Pt workfunction
together with the change in the depletion layer of the TiO.sub.2
NCs, resulting in a larger change of the photocurrent, thus higher
sensitivity.
The faster and larger response of GaN/(TiO.sub.2--Pt) towards
H.sub.2 compared to the alcohols (as shown in FIG. 5) is due to the
fact that in the case of alcohols, hydrogen is produced after
photo-oxidation of the adsorbed alcohols, which is a two-step
process with lower yield. In the case of H.sub.2 in nitrogen, there
is a direct availability of H.sub.2 molecules.
GaN/(TiO.sub.2--Pt) sensors are not sensitive to high
carbon-containing (C>2) alcohols such as propanol and butanol.
In this regard, it has been shown that the hydrogen production from
the photocatalytic oxidation of alcohols on TiO.sub.2/Pt surface is
related to the polarity of the alcohols (i.e., the higher the
polarity of the alcohol the greater the yield of photocatalytic
hydrogen production) (see Yang Y Z et al. (2006) "Photo-Catalytic
Production of Hydrogen Form Ethanol over M/TiO.sub.2 Catalysts
(M=Pd, Pt or Rh)," Applied Catalysis B: Environmental 67:217-222).
The polarity (Y) is defined as Y=( .sub.s-1)/( .sub.s+2), where
.sub.s is the relative permittivity of the solvent. Table IV lists
the polarity of various alcohols tested.
TABLE-US-00004 TABLE IV Solvent Polarity of Various Alcohols
Solvent Polarity Methanol 0.91 Ethanol 0.89 n-Propanol 0.86
i-Propanol 0.85 Butanol 0.84
The relative difficulty of producing hydrogen from higher
carbon-containing alcohols (C>2) is believed to be the cause of
the GaN/(TiO.sub.2--Pt) sensor's inability to detect alcohols with
C greater than 2. The sensor's greater response to methanol than
ethanol (at least for concentrations above 500 .mu.mol/mol) is also
consistent with the polarities of the alcohols.
The GaN/(TiO.sub.2--Pt) hybrid sensors are operable at
room-temperature sensing of hydrogen, and thus are suitable for
various applications (e.g., industrial production facilities, oil
refineries, hydrogen monitoring in hydrogen-powered vehicles,
alcohol monitoring systems for industrial and law-enforcement
purposes, etc.). The disclosed mechanisms and methods may be
implemented for achieving other multicomponent NWNC based sensors.
For example, the dynamic response of a ZnO--Pd--Ag based sensor
exposed to H.sub.2 at room temperature is illustrated in FIG. 52.
Through combinations of metal and metal-oxides available, a library
of sensors may be produced, each with precisely tuned selectivity,
on a single chip for detecting a wide variety of analytes in many
different environments.
Thus, an inactive semiconductor nanostructure (e.g., NW) surface
may be functionalized with selected analyte-specific active
metal-oxide nanoparticles. For example, another embodiment of the
present invention provides for alcohol sensors using gallium
nitride (GaN) nanowires (NWs) functionalized with zinc oxide (ZnO)
nanoparticles. The dynamic response of exemplary ZnO based sensors
exposed to benzene (concentration 500 ppm) and hexane
(concentration 100 ppm) at room temperature is shown in FIG. 51,
plates (b) and (c). The disclosed sensors operate at room
temperature, are fully recoverable, and demonstrate a response and
recovery time on the order of 100 seconds or less. The sensing is
assisted by ultraviolet (UV) light within the 215-400 nm band and
with the intensity of 375 nW/cm.sup.2 measured at 365 nm.
As discussed above, the conductivity model of GaN nanostructure is
comprised of a conducting channel surrounded by a surface depletion
region, where modulation in the width of the depletion region
induces a change in the conductivity of the NW. Similarly, ZnO
nanoparticles have a surface depletion layer, which enhances upon
exposure to air due to electron capture by surface-adsorbed oxygen.
When UV light is turned on, the photogenerated holes in ZnO assist
in removing the adsorbed oxygen, thus releasing the electrons
captured by surface oxygen back into ZnO. The photoinduced excess
of electrons in the ZnO nanoparticles promotes photogenerated
charge separation in the GaN nanostructure, thereby resulting in
increased conductivity. Conversely, there is a reduction in the
number of free electrons in the ZnO nanoparticles when exposed to
air, leading to a reduced conductivity. As seen in FIG. 6, this
effect increases with increasing flow rate of air due to enhanced
coverage of the device surface with adsorbed oxygen.
The device response to alcohols may be explained by the following
generic reaction occurring on the surface of ZnO:
2CH.sub.3OH+O.sup.-.sub.2(adsorbed).fwdarw.2HCHO+2H.sub.2O+e.sup.-
(Equation 6)
As shown in FIG. 7, the exposure to alcohol vapors leads to
increased device conductivity due to the removal of adsorbed
oxygen. In the case of exposure to N.sub.2, although there is no
surface reaction, N.sub.2 assists in desorption of the oxygen, thus
restoring the conductivity, as shown in FIG. 8.
The disclosed hybrid GaN nanostructure/ZnO nanoparticle devices are
suitable for UV-assisted alcohol sensing at room temperature. These
devices are a suitable candidate for making nanosensor arrays
because of their tunable selectivity, ability to detect the pbb
level of analytes, and fast response and recovery time.
The disclosed hybrid chemiresistive architectures utilizing
nanoengineered wide-bandgap semiconductor backbone functionalized
with multicomponent photocatalytic nanoclusters of metal-oxides
and/or metals are particularly suitable for larger scale
manufacturing techniques, such as for commercial applications. The
sensors operate at room-temperature via photoenabled sensing. A
substantial benefit of the disclosed sensors is the utilization of
all standard microfabrication techniques, thus resulting in
economical, multianalyte single-chip sensor solution. By combining
the "designer" adsorption properties of multicomponent nanoclusters
together with sensitive transduction capability of nanostructured
semiconductor backbones, photoenabled, room temperature,
ultra-sensitive, and highly selective chemical sensors are
achieved.
The sub-micron structures may be formed on an epitaxial thin-film
grown on non-conductive/semi-insulating substrate using deep UV
lithography and a combination of plasma etching and wet-etching.
Such structures are functionalized with multicomponent nanoclusters
of metal-oxides and metals using reactive-sputter deposition, as
noted above.
Referring to FIG. 9, an exemplary structure of a
semiconductor-nanocluster hybrid sensor is illustrated. Referring
to FIG. 9, plate (a), the sensor may comprise a two-terminal
sub-micron wide semiconductor backbone, functionalized with
nanoclusters of metal-oxides and/or metals. For example, the sensor
may include a lightly-doped 0.8-0.25 .mu.m wide semiconductor
two-terminal structure on a non-conductive substrate (e.g.
sapphire) formed using traditional deep UV photolithography and
plasma etching. Functionalization is a discontinuous layer of
multicomponent nanoclusters (e.g., each nanocluster comprising one
or more photocatalytic metal-oxide nanoclusters (diameter 20 nm and
smaller) and smaller metal nanoparticles (5 nm and smaller)
deposited on top of it). The multicomponent design may include more
than one oxide and metal types in the nanoclusters, and exhibits
tailored adsorption properties by virtue of the multicomponent
design. The functionalization layer is deposited using reactive
sputtering technique followed by thermal treatment--all standard
semiconductor microfabrication processes. The sensors work with
low-intensity light, such as from an LED. The emission wavelength
is determined by the semiconductor and metal-oxide bandgaps. FIG.
9, plate (b) illustrates schematically an exemplary thin-film
device including a semiconductor backbone functionalized with
TiO.sub.2 on a sapphire substrate. The smoothness of the substrate
and film after thermal processing is shown in FIG. 9, plates (c)
and (d).
Surface defects of metal-oxides are the active sites for adsorption
of various chemicals. However, at room-temperature the adsorbed
oxygen and water are very stable. This necessitates heating in
traditional metal-oxides sensors. Most metal-oxides are well-know
photocatalysts, with photoexcitation wavelengths in the range of
ultraviolet to visible, corresponding to the material bandgap. A
disclosed approach uses dynamic surface-defects generation in the
metal-oxide cluster through illumination, which allows for
efficient photodesorption of adsorbed water and oxygen. This has at
least two benefits: 1) low-power, room-temperature operation, which
also increases the lifetime of the sensors, and 2) real-time
dynamic range modulation by changing the intensity of light (for
ppt level detection the intensity of the LED can be increased as
compared to ppm level detection).
The sensor architecture provides for the combination of a
crystalline top-down fabricated semiconductor backbone with a
discontinuous nanocluster surface layer. In metal-oxide gas
sensors, the resistance changes due to diffusion and adsorption of
gases along the grain boundaries. As the present architecture uses
a discontinuous, nano-island like metal-oxide layer, the bottleneck
of gas diffusion through grain boundaries, as in traditional
metal-oxide sensors, is not present. This makes the disclosed
sensors respond relatively fast as compared to conventional
sensors, and operable at room-temperature. Unlike traditional
metal-oxide sensors, the disclosed design provides that the current
is carried by the high-quality, high mobility semiconductor
backbone, which makes the sensor fast. Also, the absence of
conduction in the nanocluster layer makes the active layer
inherently stable as compared to traditional metal-oxide thin film
sensors (e.g., grain boundary motion, defect generation and
propagation, and reduction of the metal-oxide layer is not possible
due to the absence of a "closed-circuit").
Due to the nanocluster layer of the disclosed sensors, designed
with a specific adsorption profile, they are extremely efficient in
adsorbing target analytes. This enables the design of
highly-selective sensors. Two component, three component, four
component, or five or more component cluster designs are possible
for unprecedented selectivity tailoring.
Most semiconductors have depletion regions associated with them.
The surface band bending, which is a consequence of the surface
depletion, facilitates the diffusion of the photogenerated holes to
the surface. This separation of carriers effectively suppresses
their recombination. The degree of separation is determined by the
surface potential modification by the clusters. Such separation of
photocarriers increases their lifetimes, leading to higher
photocurrent and thus sensitivity towards such surface potential
modifications. The processes that enable sensing of different
adsorbed molecules with the disclosed multicomponent nanocluster
functionalization is shown schematically in FIG. 10.
Assuming typical values of the response/recovery times for 500 ppt
of NO.sub.2, from the kinetic theory of gases the flux F of
NO.sub.2 arriving on a surface is given by the formula:
.times..times..pi..times..times..times..times. ##EQU00001##
where N.sub.A is the Avagadros' number, M is the average molar
weight of the molecule, P is the pressure, T is the temperature,
and R is the gas constant.
For 500 ppt concentration of NO.sub.2 in air, three molecules of
NO.sub.2 are impinging on a 20 nm diameter metal-oxide cluster per
second. Now, the residence time .tau. of an adsorbate at
temperature T on a surface is given by the relation
.tau.=.tau..sub.0 exp(.DELTA.H.sub.ads/RT), where .DELTA.H.sub.ads
is the heat of adsorption, and to is correlated with surface atom
vibration (roughly 10.sup.-12 s). Thus, at 298 K the residence time
for NO.sub.2 molecule on WO.sub.3 nanocluster is approximately 15
seconds (considering .DELTA.H.sub.ads for NO.sub.2 on WO.sub.3 to
be 18 kcal/mol). Considering roughly 10.sup.21 cm.sup.-3 of defect
density for typical metal oxides, results in roughly 300 adsorption
sites on a 20 nm diameter nanocluster. Assuming sticking
coefficient of 1, by 110 seconds the surface defects are saturated.
Thus, response time may be estimated to be in the order to 100
seconds, and recovery time in the order to 15-30 seconds. Although
the design of the nanocluster is described from pure thermodynamic
standpoint, other surface kinetics (such as diffusion, desorption)
may also be considered.
For fabricating the sensor backbone, un-doped (1.times.10.sup.16
cm.sup.-3) to lightly doped (1.times.10.sup.17 cm.sup.-3)
semiconductor epitaxial layer (1 .mu.m thick) on
sapphire/insulating/semi-insulating substrates may be utilized, as
shown in FIG. 11. Lower doping is needed for the sensors to be
photo enabled. The thickness of buffer layer controls the defects
arising from lattice and thermal mismatch. Ideally suited layer
structures require a relatively thin buffer layer (e.g., about 250
nm) to suppress the parasitic conduction in the buffer layer.
Similar designs may also be provided with other direct gap
semiconductors, such as ZnO, InN, AlGaN and virtually any other
direct gap semiconductor material.
The design of submicron semiconductor backbone including physical
layout and geometry is described with reference to FIG. 12. Both
serial and parallel architectures for the semiconducting resistive
backbone have unique advantages and disadvantages as the
chemiresistor backbone. Serial architecture has higher resistance
which results in lower-power operation, whereas parallel
architecture produces more robust devices insensitive to material
quality variation in the individual sections. However, the
calculation will show that the response R is the same for both
serial and parallel architecture:
.times..times. ##EQU00002##
wherein R.sub.analyte and R.sub.air are the resistances in presence
of analyte and in air, respectively. However, the resolution of the
sensor (i.e., smallest change in concentration it can measure as
required for proposed large dynamic range sensors) is greater in a
serial architecture.
The series sensor element provides for a meander shape, with
integrated passive sections as real-time calibration elements. An
exemplary design is shown in FIG. 13, plate (a). The surface
area-volume ratio for this structure is roughly 3.1. The sidewalls
of the backbone may be intentionally angled, such as at 85.degree.
as shown in FIG. 13, plate (b). This ensures uniform coverage of
the nanoclusters on the sidewalls of the structure, and also
ensures uniform photoexcitation of the semiconductor backbone. The
device is biased by a standard three dc voltage source (two AA
batteries in series) and the sensor output is the voltage measured
between the pads +V.sub.sensor and ground. The design provides
various benefits including: 1) high sensitivity and resolution; 2)
low-power consumption; 3) simplified interface circuit; and 4)
ability for real-time base-line drift calibration and temperature
compensation even in presence of analytes.
Using circuit analysis, it can be shown that Sensitivity S (as
defined in FIG. 14) may be simplified considering R.sub.L<<R
as:
.times..times..times..DELTA..times..times..times..times.
##EQU00003## wherein R.sub.L is the external low-noise precision
load resistance (e.g., see FIG. 13, plate (a)), N is the number of
segments, R is the resistance without analyte of single segment,
and .DELTA.R is the resistance change of the single segment in
presence of the analyte, and V.sub.dc is the dc source voltage.
Thus for higher sensitivity, N should be small, and R.sub.L and
V.sub.dc should be large. However, resolution of a sensor is the
smallest change in concentration of the analyte it can measure (it
is different from lowest detection limit), and is often limited by
the noise. Considering only thermal noise current in the total
sensor, the output sensor voltage noise can be expressed as:
.function..times..times..times..times..times..DELTA..times..times..times.-
.times. ##EQU00004##
wherein k.sub.B is the Boltzmann Constant, T is the temperature,
and .DELTA.f is the bandwidth. Considering both Equations 9 and 10,
the tradeoff between high sensitivity and resolution is clear. The
effect of N (i.e., number of segments) on the sensor performances
such as sensitivity, detection limits, and resolution, may be
investigated.
Referring again to FIG. 13, plate (a), the resistance of the active
sensor area may be computed using the formula, neglecting the
bends:
.apprxeq..rho..times..times..times..times..times. ##EQU00005##
wherein .rho.=1/(nq.mu.), .rho. is the resistivity, n is the
carrier concentration, and is the mobility (see also dimensions
shown in FIG. 13, plate (b)).
For example, for the GaN backbone with dimensions shown in FIG. 13,
the active-area photoresistance under 365 nm excitation from LED is
.apprxeq.60 k.OMEGA., assuming a mobility of 300 cm.sup.2V.sup.-1
s.sup.-1 and electron concentration of 1.times.10.sup.17 cm.sup.-3.
The device is considered to be excited by low-intensity (10
.mu.W/cm.sup.2) 365 nm LED. The GaN absorption coefficient
.alpha.=10.sup.5 cm.sup.-1 for the 365 nm photon is assumed. If the
sensor is biased with 3 V dc and with an external 10 K.OMEGA.
resistor, the power dissipation is approximately only 40 .mu.W. The
sensor power dissipation when in offstate (LED turned off and the
sensor has only dark current) is even lower. The total power
requirement for the sensor must also include the power required for
LED operation. There are several low-power UV (365 nm) LEDs (FOX
GROUP) that could be run by LED drivers. Power dissipation for the
LED could be low as 0.5 mW, if we drive the LED for very low
intensity. Using a LED driver to control the intensity has an added
benefit of the real-time dynamic range configuration.
The simplified chemiresistive architecture lends itself easily to
integration with interface devices as compared to more complex
devices such as metal-oxide-semiconductor field-effect transistors
(MOSFETs). The nano-watt operation amplifier (OP-Amp) TS1001 from
Touchstone Semiconductor is identified, which can provide a gain of
100 when operated in single-input voltage amplifier configuration.
The Op-Amp operated from a single AA battery dissipated about 1
.mu.W.
In one implementation, a feature of the present design is the
inclusion of the voltage probes (V.sub.cal) for calibration of base
line drift of the photoresistance of the total structure. As the
area under the calibration probes is encapsulated with thick
SiO.sub.2, the voltage drop (V.sub.cal) for a fixed intensity of
illumination through the entire structure will enable compensation
for drift in the baseline photoresistance arising from persistence
photoconductivity or temperature-induced drift.
Another feature of the present design is the "tailored" adsorption
profile through the multicomponent nanocluster design, as described
above. The design provides for suppressing the competitive
adsorption of an interfering chemical on a surface with two
different adsorption profiles, which is achieved using a primary
and a secondary component.
In this regard, FIG. 16 illustrates an exemplary multicomponent
design for the target analyte of NO.sub.2 and for the interfering
chemical of CO.sub.2. Adsorption profile for another target analyte
or set of analytes along with a set of interfering chemicals may
alternatively be provided utilizing a similar configuration. The
primary metal-oxide component is chosen so that the heat of
adsorption of NO.sub.2 on its surface is large compared to
CO.sub.2. The secondary component (e.g., the metal) is chosen with
the heat of adsorption for CO.sub.2 larger than the metal-oxide.
Thus NO.sub.2 and CO.sub.2 preferentially adsorb on the metal-oxide
and the metal, respectively. When NO.sub.2 is adsorbed on the
metal-oxide, it interacts with the photogenerated charge carriers,
producing modulation of the semiconductor backbone photocurrent, as
explained above. However, when CO.sub.2 is adsorbed on the metal,
due to the large concentration of electrons, there is minor change
in the cluster potential. Consideration of other effects, such as
catalytic decomposition on the metal, spill-over from the metal to
metal-oxide, and change of metal-work function due to adsorption of
gases, may also be appropriate.
Due to the highly dispersed nature of the metal phase, even if
there is a change in the physical properties of the metals, it has
only marginal impact on the cluster properties. Although the
general design principles are described, the specific designs of
the appropriate clusters may be fine-tuned for optimal performance
and selectivity. For example, Table V below demonstrates possible
cluster designs for NO.sub.2 and benzene sensing. Considering the
heat of adsorption of NO.sub.2 on WO.sub.3 and Pt, bigger WO.sub.3
clusters with much smaller and dispersed phase of Pt may be
favorable. Although, adsorption energy for NO.sub.2 is comparable
on both WO.sub.3 and Pt, due the higher surface area of metal-oxide
clusters, most of NO.sub.2 will adsorb on the WO.sub.3, whereas
CO.sub.2 will mostly adsorb on the Pt. For BTEX sensing, the
TiO.sub.2/Fe is favorable.
TABLE-US-00005 TABLE V Heat of adsorption on different candidates
for the multicomponent cluster design. Possible Cluster Designs for
NO.sub.2 sensing: Metal-Oxide/ NO.sub.2 CO.sub.2 Metals (kcal/mol)
(kcal/mol) MgO 9.0 3.5 TiO.sub.2 21.0 29 WO.sub.3 18.4 negligible
Fe(111) 64.5 69 Pt(111) 19 40.5 Possible Cluster Designs for
Benzene sensing: Metal-Oxide/ Benzene CO.sub.2 Metals (kcal/mol)
(kcal/mol) TiO.sub.2 15.2 29 Fe (111) 22 69
Note that the values in Table V are average adsorption energies at
room temperature for low adsorbate coverage. The values are
collected from experimental results (temperature programmed
desorption and calorimetric studies) and theoretical calculations
(such as density function theory). The values shown are for common
and stable oxide surfaces. Experimental heat of adsorption values
are dependent on various factors, including the morphology and
crystal orientation of the surface.
Other design considerations for the nanoclusters include:
1) Bandgap of the oxide: as single wavelength excitation is used
for both photodesorption of surface oxygen and hydroxyl species,
and for creating photocarriers in the semiconductor (e.g. GaN), the
bandgap of the oxide should be lower or equal to GaN bandgap (as
shown in FIG. 15). Candidates are shown in Table VI below.
TABLE-US-00006 TABLE VI Bandgaps of Common Metal Oxides Bandgap
Metal-Oxides (eV) MgO 7.1 TiO.sub.2 3.2 WO.sub.3 2.8
Fe.sub.2O.sub.3 2.1 V.sub.2O.sub.5 2.3 NiO 3.6 Al.sub.2O.sub.3 7.0
Candidates are in bold and underlined, E.sub.g < 3.4 eV.
2) Nature of surface defect types: surface defects (i.e. the active
adsorption sites) of metal-oxides are of three types: bronstead,
lewis-acid/base sites, and redox sties. Organic compounds such as
benzene predominantly adsorb by dehydgrogenetion (i.e., removal of
H+) requiring surface lewis sites. On the other hand, NO.sub.2
predominantly adsorbs as surface nitrate (NO.sub.3.sup.-),
requiring base sites. Most metal-oxide surfaces at room-temperature
are hydroxylated, and thus photoexcitation will increase the
concentration of one type of predominant defects.
3) Redox potentials of the oxide: redox potentials of oxides
indicate the ability of photogenerated carriers to oxidize or
reduce any adsorbed molecule. Depending on whether molecules will
be oxidized or reduced on the surface, they interact with charge
carriers differently in the clusters.
4) Stability of the adsorbates: Stability of the adsorbed species
is an important consideration, as it determines the recovery time,
and ultimately usability of the sensors. As can be seen for Fe,
where the very high adsorption energy might produce very stable NO
adsorbed species on the surface, rendering the nanoclusters
inactive after exposure to high concentrations of NO.sub.2.
4) Nature of the adsorbed species (molecular or dissociative):
nature of the adsorbed species determines the photochemical
reaction pathways and ultimately the sensitivity. Additional
multicomponent nanocluster designs for NO.sub.2 and BTEX sensing
are shown in Table VII.
TABLE-US-00007 TABLE VII Possible designs of nanoclusters
Metal-Oxides/ Target Metal Analyte WO.sub.3/Pt NO.sub.2
TiO.sub.2/Fe BTEX
The use of heterogeneous metal-oxide supported metal catalysts in
industrial production, abatement, and remediation for the past few
decades has been extensive, and generated an exhaustive body of
literature that may be readily utilized for nanocluster designs
according to the present invention. Indeed, some of the systems are
well-understood, so that a desired selectivity outcome may be
readily predicted. The well-known strong metal/support interactions
(SMSI) effects in heterocatalysts are different, as the metals are
not reduced on the oxides in the disclosed devices.
Computing the size and coverage of the clusters is an important
consideration, given the size and coverage of the NCs ultimately
determines the overall sensitivity of the device. Thus,
determination of the most effective size and coverage of the
clusters is desirable. It is known that the surface area and
relative particle size has a significant effect on the catalytic
properties of metals and metal oxides. However, due to the presence
of metals on the metal-oxide clusters, there will be significant
depletion of the metal-oxide clusters. Thus, overly small
metal-oxide clusters would be substantially depleted and hamper
effectiveness, whereas overly large clusters would also result in
lower sensitivity. Consideration of the nature of the depletion
regions formed by such nano-sized metal clusters on a semiconductor
is therefore prudent.
The classical Schottky model depletion theory cannot predict
accurately the zero-bias depletion width produced by metallic
nanoclusters on a semiconductor. According to Zhdanov's model, the
depletion depth associated with such metal nanoclusters on a
semiconductor can be estimated by the following relationship:
.times..times..times..pi..times..times..times..times..times.
##EQU00006##
wherein w.sub.d is the depletion width, r.sub.c is the radius of
the nanocluster, V.sub.bi is the built-in voltage for the junction,
q is the elementary charge, and N.sub.d is the dopant concentration
in the semiconductor.
The plot in FIG. 17 demonstrates the depletion width of TiO.sub.2
clusters due to Pt particles. It is clear that 4 nm of Pt clusters
on 20 nm diameter TiO.sub.2 clusters would produce depletion of
about 5 nm in the TiO.sub.2.
Coverage of the metal-oxide nanocluster functionalization is
determined by the limit of formation of continues metal-oxide film.
The coverage is dependent on various parameters such as metal-oxide
wetting of the semiconductor, morphology of phases formed after
thermal treatment, etc., and may be verified by SEM imaging. The
metal coverage should be sparse to ensure only partial depletion of
the clusters.
With regard to fabrication, techniques such as wet chemical etching
may not be suitable for etching nanoscale, high aspect-ratio
nanostructures due to undercutting of the mask and sloped
sidewalls. Hence, the development of a dry etching process with
relatively less low damage and precise-depth control capability is
preferred for the fabrication of nanostructures. Such etching of
semiconductor nanostructures is described in further detail in
Example 4 below.
Referring to FIG. 18, the components for an exemplar interface
circuit is illustrated. The LED intensity may be controlled by the
microcontroller (MAXQ3213, with a LED driver). By relatively simple
design change of a selected multicomponent cluster, different
applications are readily provided. In addition, using wide bandgap
material as a backbone enables the sensor to work at elevated
temperatures, and in presence of radiation and other harsh
environmental conditions.
As shown in Table VIII below, the possible designs of the
multi-component nanoclusters are virtually unlimited, resulting in
the ability to provide sensors for numerous applications.
TABLE-US-00008 TABLE VIII Exemplary Designs of Multicomponent
Nanoclusters Nanocluster Components: Semiconductor Metal Oxide:
Metal: GaN Titanium Oxide Titanium InN Tin Oxide Nickel AlGaN Iron
Oxide Chromium Magnesium Oxide Cobalt Vanadium Oxide Ruthenium
Nickel Oxide Rhodium ZnO Zirconium Oxide Gold InAs Aluminum Oxide
Silver Copper Oxide Platinum Zinc Oxide Palladium Strontium Oxide
Vandium
Thus, in accordance with the disclosed methodologies, sensor
devices suitable for a wide range of applications are achieved.
Further, the particular architecture of the sensor devices may be
readily tailored for the desired application and associated
conditions, as well as one or multiple active sensor elements
configured for sensing particle targets. For example, an exemplary
sensor device includes eight individually addressable active sensor
elements, as shown in FIG. 53, which can each detect a different
target analyte (e.g., various gases). The sensor device may include
an on-chip calibration element for automatic drift compensation.
The sensor device may also include an on-chip micro-heater, as
shown in FIG. 54, for stabilizing temperature and/or humidity. The
temperature profiles of a 50 .mu.m microheater made from a Ti/Ni
metal stack MH recorded at 5 V bias voltage and 10 V bias voltage
are shown in FIG. 55, plates (a) and (b), respectively.
Thus, the disclosed sensor devices may comprise various active
sensor elements and passive elements for formation of on-chip
circuits. Multiple active elements may be provided with a
combination of different functionalization to detect multiple gases
in a single chip. The chip may include precise passive elements
(elements which have the same semiconductor backbone but passivated
from the environment), for calibration on the same chip, which has
the same temperature coefficient for current as the active sensor
element. Thus, any change due to the temperature or aging can be a
calibrated out using the on-chip calibration element(s). Using such
on-chip components (e.g., see FIG. 53), bridge circuits may be
provided directly on the chip, allowing for sensor devices with
high resolution.
Although the sensor devices may comprise a micro-heater element as
noted above, such element is not required. The disclosed sensor
devices do not need to be heated for sensing, and are capable of
sensing a host of gases at room temperature. Total power
consumption is extremely low (e.g., an exemplary 8 active sensor
element device provided for a total power consumption about 10
microwatts. Further, the disclosed sensor devices are stable and
recoverable even in the presence of corrosive gases (e.g, HCN,
CL.sub.2, HCl, etc), and capable of withstanding very high gas
concentrations. The sensor devices are also capable of operating in
oxygen rich or relatively lean conditions.
In accordance with disclosed embodiments, the active sensor(s)
elements are designed by first selecting a nanoclusters and/or a
layer of a base photocatalytic metal oxide (e.g., TiO.sub.2,
V.sub.2O.sub.5, Cr.sub.2O.sub.3, Fe.sub.2O.sub.3, CoO, NiO, CuO,
ZnO, ZrO.sub.2, WO.sub.3, MoO.sub.3, SnO.sub.2). Nanoclusters of a
catalytic metal (e.g., Ti, V, Cr, Fe, Co, Ni, Cu, Al, Zr, Nb, Mo,
Ru, Rh, Pd, Ag, Hf, Ta, W, Re, Ir, Pt, Au) are then applied on top
of the base photocatalytic metal oxide nanoclusters. Alternatively
in other embodiments, nanoclusters of a second photocatalytic metal
oxide different than the base metal oxide are applied on top of the
base metal oxide, providing for dual metal oxide
functionalizations. Thus, the sensor element comprises a base layer
or nanoclusters of a first metal-oxide, and nanoclusters of a
second metal oxide or metal. The selection of the particular metal
oxide and metal provides for the desired selectively.
For example, the dynamic response of functionalized GaN NW with
selected metal oxide for selectively sensing hydrogen sulfide
(H.sub.2S) in dry air is shown in FIG. 56. The response of the
functionalized GaN NW for sensing NO.sub.2 in dry air is shown in
FIG. 57. The response of the functionalized GaN NW for sensing
SO.sub.2 in dry air is shown in FIG. 58. The response of the
functionalized GaN NW for sensing CO.sub.2 in dry air using the
metal oxide sensor devices of the present invention is shown in
FIG. 59. Thus, a wide range of target gases, from reducing to
oxidizing to inert gases, is achieved.
A summary of operational and performance specifications of sensing
devices in accordance with disclosed embodiments is set forth in
Table IX below:
TABLE-US-00009 Range of Response (%) = Analyte Detection (R.sub.gas
- R.sub.air/R.sub.air) Ammonia 1-100 ppm 15 Chlorine 0.5-10 ppm 212
Hydrogen chloride 1-100 ppm 74 Hydrogen cyanide 1-100 ppm 10
Hydrogen sulphide 10-1000 ppm 20 Hydrogen 0.5-10% 500 Oxygen 10-30%
40 Carbon dioxide 01.-1% 2 Carbon monoxide 10-300 ppm 15 Nitrogen
dioxide 100-500 ppm 2 Nitric oxide 5-1000 ppm 2.6 Methane 50-5000
ppm 9
The disclosed devices are suitable for environmental monitoring,
hazmat, large-scale industrial monitoring and control, explosive
threat detection, and other markets where rapid detection of gases
and chemicals in air is desired. Compared to conventional sensors,
the disclosed sensors of the present invention are extremely small
(e.g., 4 mm.times.4 mm, or 2.5 mm.times.2.5 mm, or smaller) and
inexpensive, exhibit low power consumption (e.g., less than 100
microwatts, and in some embodiments less than about 10 microwatts),
but capable of sensing a large dynamic range (e.g., 100 parts per
billion to >2%), detect a variety of chemicals under various
conditions with no cross-sensitivity (thus minimizing false
positives), and exhibit a long operating life. In addition, the
disclosed sensors of the present invention may be manufactured
using the same manufacturing methodologies utilized for producing
conventional integrated circuits. An exemplary sensor module is
shown in FIG. 60, which has dimensions of about 8 cm.times.6
cm.times.1 cm, a weight of 0.4 pounds, power consumption
requirements for continuous operation of about 0.2 watts, eight
active sensor elements or channels for simultaneous measurement of
eight different target gases, and including a built-in air sampling
element with microblower.
The disclosed sensor devices may be installed in residential and
commercial buildings for on-demand ventilation control, resulting
in a decrease in energy consumption. The sensors can detect the
presence of harmful VOCs (Benzene, Xylene, and formaldehyde), which
are often emitted by building materials, paints, and furniture, and
are also associated with human metabolism. After detecting an
increase in the levels of targeted harmful chemicals, the
ventilation system may be adjusted for safety, comfort and health
of the occupants. Alternatively or in addition, the sensors could
monitor CO levels and gas leaks in buildings for safety. Thus, the
disclosed sensor technology may be readily implemented in indoor
monitoring systems, thereby generating large cost savings in terms
of energy efficiency, health of the occupants, and low-maintenance
costs.
In case of accidental release of chemicals, the disclosed sensors
are suitable for use by first-responders to detect the presence of
chemicals and associated hazards. Thus, the challenges of a
disaster may be managed more safely and efficiently. The disclosed
hybrid sensor technology may be implemented in ultra-small,
handheld units, which identify multiple hazardous materials with
low power consumption. Such devices would be ideal for first
responders.
The disclosed sensors are also suitable for industrial monitoring
applications. For example, the sensors may be used for monitoring
different gases for process control in industrial facilities such
as oil refineries, manufacturing plants, etc. They may be installed
at various points throughout an industrial facility for point
detection for leaks of toxic chemicals. The may also be implemented
in personal monitoring devices for recording personal exposure
levels for compliance purposes with state and federal maximum
exposure level regulations. The disclosed technology therefore
promises unlimited control over the sensor design, thus having the
ability to produce sensors for various different industries and
processes.
Implementations of the disclosed technology for law enforcement and
safety applications are also provided. For example, the disclosed
sensors may be utilized in breath analyzers for law-enforcement and
individual use. The hybrid sensors may also be integrated into
hand-held devices (e.g., cell phones) as plug-in modules to
existing devices. For example, the disclosed sensor may be
integrated into a hand-held device to enable a user to check his or
her blood alcohol level.
Implementations of the disclosed sensor technology are also
suitable for defense and security applications. The sensors may be
used for safety monitoring in public places such as subway/rail
stations, airports, public buildings, and in transit systems. For
example, the sensors may be utilized to monitor and detect
deliberate release of harmful chemicals and explosives, thus
protecting civilians from attacks. They may also be integrated into
equipment carried or worn by soldiers for detection of harmful
chemicals, explosives, or other terrorist elements.
Having generally described the invention, the same will be further
understood through reference to the following additional examples,
which are provided by way of illustration and are not intended to
be limiting of the present invention unless specified.
EXAMPLES
Example 1
Nanowire-nanocluster hybrid chemical sensors were realized by
functionalizing gallium nitride (GaN) nanowires (NWs) with titanium
dioxide (TiO.sub.2) nanoclusters for selectively sensing benzene
and other related aromatic compounds.
Materials and Methods
C-axis, n-type, Si-doped GaN grown by catalyst-free molecular beam
epitaxy on Si (111) substrates were utilized. For details of NW
growth, see Bertness K A et al. (2008) "Mechanism for spontaneous
growth of GaN nanowires with molecular beam epitaxy," J. Crystal
Growth 310(13):3154-3158). An exemplary process of sensor
fabrication is shown in FIG. 19. Post-growth device fabrication was
done by dielectrophoretically aligning the nanowires on 9
mm.times.9 mm sapphire substrates (see Motayed A et al. (2006)
"Realization of reliable GaN nanowire transistors utilizing
dielectrophoretic alignment technique," J. Appl. Phy. 100:114310).
The device substrates had 12 nm thick Ti alignment electrodes of
semi-circular geometry with gaps between them ranging from 4 .mu.m
to 8 .mu.m. After the alignment of the nanowires, the samples were
dried at 75.degree. C. for 10 min on a hot plate for evaporation of
the residual solvent. This was followed by a plasma enhanced
chemical vapor deposition (PECVD) of 50 nm of SiO.sub.2, at a
deposition temperature of 300.degree. C. This passivation layer was
deposited to ensure higher yield for the fabrication process.
After the oxide deposition, photolithography was performed to
define openings for the top contact. The oxide in the openings was
etched using reactive ion etching (RIE) with
CF.sub.4/CHF.sub.3/O.sub.2 (50 sccm/25 sccm/5 sccm) gas chemistry.
The top contact metallization was deposited in an electron-beam
evaporator with base pressure of 10.sup.-5 Pa. The deposition
sequence was Ti (70 nm)/Al (70 nm)/Ti (40 nm)/Au (40 nm). The oxide
layer over the nanowires between the end contacts was then etched
in buffered HF etching solution for 15 seconds. A negative resist
was used to protect the end metal contacts from the etching
solution.
The TiO.sub.2 nanoclusters were deposited on the exposed GaN NWs
using RF magnetron sputtering. The deposition was done at
325.degree. C. with 50 sccm of Ar flow, and 300 W RF power. The
deposition rate was about 0.2 .ANG./s. Thermal annealing of the
complete sensor devices (GaN NW with TiO.sub.2 nanoclusters) was
done at 650.degree. C. to 700.degree. C. for 30 seconds in a rapid
thermal processing system with 6 slpm (standard liter per min) flow
of ultrahigh purity Ar. A relatively slow ramp rate of 100.degree.
C. per min was chosen to reduce the stress in the metal-nanowire
contact area during heating. The anneal step was optimized to
facilitate Ohmic contact formation to the GaN NWs and also to
induce crystallization of the TiO.sub.2 clusters. Additional
lithography was performed to form thick metal bond pads with Ti (40
nm) and Au (160 nm).
The crystallinity and phase analysis of the sputtered TiO.sub.2
films were assessed by X-ray diffraction (XRD). The XRD scans were
collected on a Bruker-AXS D8 scanning X-ray micro-diffractometer
equipped with a general area detector diffraction system (GADDS)
using Cu-K.alpha. radiation. The two-dimensional 2.THETA.-.chi.
patterns were collected in the 2.THETA.=23.degree. to 510 range
followed by integration into conventional .OMEGA.-.THETA. scans.
The microstructure and morphology of the sputtered TiO.sub.2 films
used for fabrication of sensors were characterized by
high-resolution analytical transmission and scanning transmission
electron microscopy (HRTEM/STEM) and cold field-emission scanning
electron microscopy (FESEM). GaN nanowires with sputtered TiO.sub.2
were deposited onto a lacey carbon films supported by Cu-mesh grids
and analyzed in a 300 kV TEM/STEM microscope. The instrument was
equipped with an X-ray energy dispersive spectrometer (XEDS) and an
electron energy-loss spectrometer (EELS) as well as bright-field
(BF) and annular dark-field (ADF) STEM detectors to perform spot
and line profile analyses.
The device substrates, i.e., the sensor chips, were wire-bonded on
a 24 pin ceramic package for the gas sensing measurements. The
device characterization and the time dependent sensing measurements
were done using an Agilent B1500A semiconductor parameter analyzer.
Each sensor chip was placed in a custom-designed stainless steel
test chamber of volume 0.73 cm.sup.3 with separate gas inlet and
outlet. The test chamber had a quartz window on top for UV
excitation provided by a 25 W deuterium bulb (DH-2000-BAL, Ocean
Optics) connected to a 600 .mu.m diameter optical fiber cable with
a collimating lens at the end for uniform illumination over the
sample surface. The operating wavelength range of the bulb was 215
to 400 nm. The intensity at 365 nm measured using an optical power
meter was 375 nW cm.sup.-2. For all the sensing experiments regular
breathing air (<9 ppm of water) was used as the carrier gas. A
wide range of concentrations from 1% to as low as 50 parts per
billion (ppb) of various organic compounds were achieved with a
specific arrangement of bubbler and mass flow controllers (MFCs).
During the sensor measurements, the net flow (air+VOC mix) into the
test chamber was set to a constant value of 20 sccm. After the
sensor devices were exposed to the organic compounds, they were
allowed to regain their baseline current with the air-chemical
mixture turned-off, without purging or evacuating the
test-chamber.
Results
FIG. 20 shows GaN nanowires with three different nominal
thicknesses of TiO.sub.2 coatings sputtered on them: 2 nm (FIG. 20,
plate (a)); 5 nm (FIG. 20, plate (b)); and 8 nm (FIG. 20, plate
(c)). Rather sparse, well-defined clusters can be seen for both the
5 nm and 8 nm area-averaged sputtered coatings of TiO.sub.2. The
average size of these large clusters was about 15 nm. For the 8 nm
sputtered coating, the coverage of the TiO.sub.2 clusters is much
denser. However, TEM studies revealed the presence of clusters with
much smaller diameter (less than about 4 nm) on the nanowire
surface.
Detection of XRD signal from the TiO.sub.2 decorated GaN NWs was
difficult due to the minuscule size and total volume of TiO.sub.2
nanoclusters. We therefore prepared a 150 nm thick TiO.sub.2 film
by sputtering it onto a SiO.sub.2 coated Si substrate at
300.degree. C. followed by anneal at 650.degree. C. for 45 s in
argon. The processing conditions produced an identical morphology
as in the TiO.sub.2 decorated NW case. Referring to FIG. 21, we
identified from the XRD that TiO.sub.2 is in the single-phase
anatase form. As-deposited TiO.sub.2 films were found to be
amorphous.
The XRD results agree with the TEM analysis on TiO.sub.2 decorated
GaN NWs, which revealed that upon annealing at 700.degree. C. for
30 s, the TiO.sub.2 islands became partially crystalline, as shown
in FIG. 22. Three most common phases of TiO.sub.2 are anatase,
rutile, and brookite. Thermodynamic calculations predict that
rutile is the most stable TiO.sub.2 phase in the bulk state at all
temperatures and atmospheric pressure (see Norotsky A et al. (1967)
"Enthalpy of Transformation of a High-Pressure Polymorph of
Titanium Dioxide to the Rutile Modification," Science 158:338;
Jamieson J C and Olinger B (1969) "Pressure-temperature studies of
anatase, brookite, rutile, and TiO.sub.2(II); A discussion," Am.
Min. 54:1477-1480). However, comparative experiments with particle
size showed that the phase stability might reverse with decreasing
particle size, possibly due to the influence of surface free energy
and surface stress (Zhang H Z and Banfield J. F (2000)
"Understanding polymorphic phase transformation behavior during
growth of nanocrystalline aggregates: insights from TiO.sub.2," J.
Phys. Chem. B 104:3481-3487). Anatase is the most stable phase when
the particle size is less than about 11 nm, whereas rutile is most
stable at sizes greater than about 35 nm. Although both rutile and
anatase TiO.sub.2 are commonly used as photocatalyst, anatase form
shows greater photocatalytic activity for most reactions
(Linsbigler A L et al. (1995) "Photocatalysis on TiO.sub.2
Surfaces: Principles, Mechanisms, and Selected Results," Chem. Rev.
95:735-7; Tanaka K et al. (1991) "Effect of crystallinity of TiO2
on its photocatalytic action," Chem. Phys. Lett. 187:73-76). This
is one consideration for sputtering nominally 8 nm of TiO.sub.2 for
the sensor fabrication.
Although we have sputtered 8 nm of TiO.sub.2 for fabricating the
hybrid sensors, for the TEM studies 20 nm of TiO.sub.2 coating was
utilized. The thick GaN nanowires prevented acquisition of any TEM
diffraction from thinner TiO.sub.2 coatings. The TEM results
presented for 20 nm thick TiO.sub.2 was representative of the
clusters formed for 8 nm deposited TiO.sub.2 in actual sensors.
Typical morphologies of a 20 nm thick TiO.sub.2 film sputtered on
n-GaN nanowires and annealed at 700.degree. C. for 30 seconds are
illustrated by TEM data in FIG. 22. The TEM image in FIG. 22, plate
(a) shows 2 nm to 10 nm diameter individual TiO.sub.2 particles
non-uniformly distributed on the surface of a GaN nanowire. Some of
the particles are identified by circles. Crystallinity of some
nanoparticles observed is shown in the HRTEM image in FIG. 22,
plate (b) with nanocrystallites on the edge of a GaN nanowire with
the sputtered TiO.sub.2. The FFT pattern from the boxed area is
seen in exploded view in the upper left inset image, showing 0.35
nm lattice fringes which are consistent with a (101) reflecting
plane of anatase but not available in hexagonal wurtzite-type GaN
crystals.
Referring to FIG. 23, plate (a), a BF-STEM image shows 5 to 10 nm
TiO.sub.2 nanoparticles barely visible against the GaN nanowire. An
ADF-STEM image of a TiO.sub.2 island on a GaN nanowire is shown in
FIG. 23, plate (b). The presence of TiO.sub.2 was confirmed by
analysis of selected areas as well as of individual particles using
XEDS and EELS and nanoprobe capabilities. Referring to FIG. 23,
plate (c), the X-ray spectrum of an individual 5 nm TiO.sub.2
particle (identified by the marked circle "A" in FIG. 23, plate
(a)) exhibits the TiK.alpha. peak at 4.51 keV and the weak
OK.alpha. peak at 0.523 keV. The NK.alpha. peak at 0.39 keV and
gallium lines (the GaL series at 1.0 keV to 1.2 keV) and the
CK.alpha. peak at 0.28 keV are also identified. EEL spectrum
acquired at Position "1" marked in FIG. 23, plate (b) (the tip of a
TiO.sub.2-containing aggregate) exhibits the TiL edge at 456 eV and
the OK edge at 532 eV and also the CK edge at 284 eV. A reference
spectrum recorded at Position 2 marked in FIG. 23, plate (b) (an
edge of the GaN nanowire) reveals traces of titanium and oxygen
with the NK edge at 401 eV and the GaL edge at 1115 eV,
respectively.
FIG. 24 shows the current-voltage (I-V) characteristics of a GaN NW
two-terminal device at different stages of processing. The I-V
curves of the as-deposited devices were non-linear and asymmetric.
The current decreased when the SiO.sub.2 layer over the NW was
etched. However, the current increased with the deposition of
TiO.sub.2 nanoclusters. Oxygen adsorption on the bare GaN nanowire
surface can introduce surface states (Zywietz et al. (1999) "The
adsorption of oxygen at GaN surfaces," Appl. Phys. Lett. 74:1695),
resulting in the decrease of the nanowire conductivity. The devices
annealed at 700.degree. C. for 30 seconds showed significant
changes in their I-V characteristics with a majority of the devices
exhibiting linear I-V curves. This is consistent with the fact that
low resistance ohmic contacts to the nitrides require annealing at
700.degree. C. to 800.degree. C. (see Motayed A et al. (2003)
"Electrical, thermal, and microstructural characteristics of
Ti/Al/Ti/Au multilayer ohmic contacts to n-type GaN," J. Appl.
Phys. 93(2):1087-1094).
FIG. 25 shows the photoconductance of a bare GaN NW device and the
TiO.sub.2 coated GaN NW device. The NW devices with TiO.sub.2
nanoclusters showed almost two orders of magnitude increase in the
current when exposed to UV light as compared to the similar
diameter bare NW devices. Increase of photoconductance due to
surface functionalization has been observed in ZnO nanobelts coated
with different polymers (Lao C S et al. (2007) "Giant Enhancement
in UV Response of ZnO Nanobelts by Polymer
Surface-Functionalization," J. Am. Chem. Soc. 129:12096-12097).
This enhancement of photoconductance is often attributed to the
separation of photogenerated charge carriers by a surface depletion
field, thereby increasing the lifetime of the photogenerated
carriers. After the light is turned off, the photo current decays
rapidly, but not to the dark current value, which is likely due to
the persistent photoconductivity of the NWs (see Sanford N A et al.
(2010) "Steady-state and transient photoconductivity in c-axis GaN
nanowires grown by nitrogen-plasma-assisted molecular beam
epitaxy," J. Appl. Phy. 107:034318).
The current through the bare GaN NW devices did not change when
exposed to different VOCs mixed in air, even for concentrations as
high as few percents. On the other hand, the TiO.sub.2 coated
hybrid devices responded even to the pulses of 20 sccm airflow.
This is expected, considering that the conduction in most
metal-oxides is affected by the presence of oxygen. The response of
the TiO.sub.2 nanocluster-GaN nanowire hybrid sensor to 1000 ppm of
toluene in air is illustrated in FIG. 26. Exposure to the VOC in
the dark had no effect on the hybrid device. However, in presence
of UV excitation, when 1000 ppm of toluene (mixed in air) was
introduced into the gas chamber, the sensor photocurrent decreased
dramatically to approximately 2/3 of its base value. After 100
seconds of gas exposure, the gas flow is turned off and the sensor
is allowed to recover at room temperature without any additional
purging. The repeatability of the sensing action of these hybrid
sensors is evident from FIG. 26.
Interestingly, the hybrid sensors did not respond when exposed to
methanol, ethanol, isopropanol, chloroform, acetone, and
1,3-hexadiene, even for concentrations as high as several percent.
Also, the photocurrent for these sensors increased with respect to
air when exposed to toluene vapors, whereas for every other
aromatic compound, the photocurrent decreased relative to air, as
shown in FIG. 27, plate (a). More than twenty sensor devices were
tested, with all exhibiting the same trend. In addition, the use of
toluene from different sources resulting in the same sensor
behavior. FIG. 27, plate (b) shows the response of a different
device for 200 ppb concentrations of the same chemicals. It is
clear that even for toluene concentration as low as 200 ppb, the
relative change in photocurrent is the reverse of that observed
with other chemicals. If the photocurrent in the presence of air
for these sensors is used as their baseline calibration, then we
can distinctly identify toluene from other aromatic compounds
present in air using our hybrid devices. The response time is
defined as the time taken by the sensor current to reach 90% of the
response (I.sub.f-I.sub.0) when exposed to the analyte. The I.sub.f
is the steady sensor current level in the presence of the analyte,
and I.sub.0 is the current level without the analyte, which in our
case is in the presence of air. The recovery time is the time
required for the sensor current to recover to 30% of the response
(I.sub.f-I.sub.0) after the gas flow is turned off (Garzella C et
al. (2000) "TiO.sub.2 thin films by a novel sol-gel processing for
gas sensor applications," Sens. and Actuators B: Chemical
68:189-196). The response and recovery times for ppm levels of BTEX
concentrations were .apprxeq.60 seconds and .apprxeq.75 seconds,
respectively. The response and recovery times for ppb levels of
concentrations were .apprxeq.180 seconds and .apprxeq.150 seconds,
respectively. In contrast, conventional nanowire/nanotube sensors
reported in the literature as working at room-temperatures had much
longer response times in minutes (Leghrib R et al. (2010) "Gas
sensors based on multiwall carbon nanotubes decorated with tin
oxide nanoclusters," Sens. and Actuators B: Chemical 145:411-416;
Balazsi C et al. (2008) "Novel hexagonal WO3 nanopowder with metal
decorated carbon nanotubes as NO.sub.2 gas sensor," Sensors and
Actuators B: Chemical 133:151-155; Kuang Q et al. (2008) "Enhancing
the photon-and gas-sensing properties of a single SnO.sub.2
nanowire based nanodevice by nanoparticle surface
functionalization," J. Phys. Chem. C 112:11539-11544; Lim W et al.
(2008) "Room temperature hydrogen detection using Pd-coated GaN
nanowires," Appl. Phys. Lett. 93:072109). Fast response and
recovery times indicate fast adsorption and desorption, which is
attributed to the enhanced reactivity of the nanoscale TiO.sub.2
clusters.
The responses of two hybrid devices to different concentrations of
toluene in air are shown in FIG. 28. FIG. 28, plate (a) shows the
change of photocurrent of a 234 nm diameter device when exposed to
toluene concentrations from 10000 ppm down to 100 ppm. FIG. 28,
plate (b) shows the photocurrent of a sensor device with 170 nm
diameter wire for toluene concentrations from 1 ppm to 50 ppb.
Sensitivity is defined as (R.sub.gas-R.sub.air)/R.sub.air, where
R.sub.gas, R.sub.air are the resistances of the sensor in the
presence of the chemical-air mixture and in the presence of air,
respectively. The sensitivity plots of a hybrid device for
different VOCs tested are shown in FIG. 29. The sensitivity plot
emphasizes the ability of these hybrid sensors to reliably detect
BTEX (benzene, toluene, ethylbenzene, chlorobenzene, and xylene),
which are common indoor and outdoor pollutants with wide detection
range (50 ppb to 1%).
Example 2
The sensing behavior of three NWNC based hybrid sensors was
compared: 1) GaN NW coated with TiO.sub.2 NCs (hereafter referred
to as GaN/TiO.sub.2 NWNC hybrids); 2) GaN NW coated with TiO.sub.2
and Pt multicomponent NCs (i.e., GaN/(TiO.sub.2--Pt) NWNC hybrids);
and 3) GaN NW coated with Pt NCs (i.e., GaN/Pt NWNC hybrids). It
was found that sensors with TiO.sub.2--Pt multicomponent NCs on GaN
NW were only sensitive to methanol, ethanol, and hydrogen. Higher
carbon-containing alcohols (such as n-propanol, iso-propanol,
n-butanol) did not produce any sensor response. These sensors had
the highest sensitivity towards hydrogen. Prior to the Pt
deposition, the GaN/TiO.sub.2 NWNC hybrids did not exhibit any
response to alcohols, however they detected benzene and related
aromatic compounds such as toluene, ethylbenzene, xylene, and
chlorobenzene mixed with air. The GaN/Pt hybrids only showed
sensitivity to hydrogen and not to methanol or ethanol. The
sensitivity of GaN/Pt hybrids towards hydrogen was lower compared
to the GaN/(TiO.sub.2--Pt) hybrids.
Materials and Methods
GaN NWs utilized for this study were c-axis, n-type (Si-doped),
grown by catalyst-free molecular beam epitaxy as described by
Bertness K A et al. (2008), supra, J. Crystal Growth
310(13):3154-3158. Post-growth device fabrication was done by
dielectrophoretically aligning the nanowires on 9 mm.times.9 mm
sapphire substrates. The details of the device fabrication are set
forth in Example 1. After fabrication of two-terminal GaN NW
devices, the TiO.sub.2 NCs were deposited on the GaN NW surface
using RF magnetron sputtering. The deposition was done at
325.degree. C. with 50 standard cubic centimeters per minute (sccm)
of Ar flow, and 300 W RF power. The nominal deposition rate was
about 0.24 .ANG./s. Thermal annealing of the complete sensor
devices (GaN NW with TiO.sub.2 nanoclusters) was done at
700.degree. C. for 30 seconds in a rapid thermal processing system.
For TiO.sub.2--Pt composite NCs, the Pt was sputtered using DC
sputtering after annealing of the TiO.sub.2 clusters on GaN NW. The
Pt sputtering was done with an Ar flow of 35 sccm, at a pressure of
1.3 Pa and power of 40 W for 10 seconds. For the Pt/GaN devices Pt
was sputtered on bare GaN NWs after annealing the ohmic contacts at
700.degree. C. for 30 seconds. Additional lithography was performed
to form thick metal bond pads with Ti (40 nm) and Au (200 nm). The
device substrates, i.e., the sensor chips, were wire-bonded on a 24
pin ceramic package for the gas sensing measurements.
The microstructure and morphology of the sputtered TiO.sub.2 films
used for the fabrication of the sensors were characterized by
high-resolution transmission and scanning transmission electron
microscopy (HRTEM/STEM), selected-area electron diffraction (SAED),
and field-emission scanning electron microscopy (FESEM). For the
TEM characterization, the GaN NWs were dispersed on 10 nm thick
carbon films supported by Mo-mesh grids, followed by the deposition
of TiO.sub.2 NCs and annealing, and subsequent Pt deposition. The
samples were analyzed in a FEI Titan 80-300 TEM/STEM microscope
operating at 300 kV accelerating voltage and equipped with S-TWIN
objective lenses, which provided 0.13 nm (STEM) and 0.19 nm (TEM)
resolution by points. The instrument also had a Gatan CCD image
acquisition camera, bright-field (BF), ADF and high-angle annular
dark-field (HAADF) STEM detectors to perform spot, line profile,
and areal compositional analyses using an EDAX 300 kV
high-performance Si/Li X-ray energy dispersive spectrometer
(XEDS).
The as-fabricated sensors were placed in a custom designed gas
chamber for gas exposure measurements. The device characterization
and the time dependent sensing measurements were done using an
Agilent B1500A semiconductor parameter analyzer. The gas sensing
experiments have been performed by measuring the electrical
conductance of the devices upon exposure to controlled flow of
air/chemical mixture in presence of UV excitation (25 W deuterium
bulb operating in the 215 nm to 400 nm range). For all the sensing
experiments with chemicals, breathing air (<9 .mu.mol/mol of
water) was used as the carrier gas. For the hydrogen sensing we
used high-purity nitrogen as the carrier gas. After the sensor
devices were exposed to the organic compounds and hydrogen, they
were allowed to regain their baseline current with the air-chemical
mixture turned-off, without purging or evacuating the
test-chamber.
Results
Morphological and Structural Characterization of NWNC Hybrids
It was challenging to measure the sizes and shapes of small
TiO.sub.2 and Pt particles on the surfaces GaN NWs from greyscale
TEM images due to: a) 270 nm to 300 nm thickness of the NWs used in
the devices and variations of thickness and curvature across the
structure; b) diffraction contrast induced particularly by bending
of the wires--even similar particles could appear as having
different intensities, while local thickness variations of the
carbon support film could result in variable contrast affecting the
mean intensity values of the particles; c) overwhelming domination
of electron diffraction in SAED from the GaN NW over the
diffraction from TiO.sub.2 and Pt nanoparticles. To overcome these
problems, TEM imaging was conducted under minimal beam intensity
conditions close to the Scherzer defocus at highest available
accelerating voltage of 300 kV using both stationary beam
(bright-field TEM/SAED, phase-contrast high-resolution TEM) and
scanning beam (STEM/XEDS) modes. Areas for analyses were selected
near the wire's edges and on the amorphous carbon support film in
the vicinity of the NWs.
FIG. 30 shows HRTEM micrographs of a GaN NW on a thin amorphous
carbon support films with TiO.sub.2 coating, before and after the
Pt deposition. The deposited TiO.sub.2 layer formed an island-like
film, where 10 nm to 50 nm partially aggregated particles (see FIG.
30, plate (a)) were often interconnected into extended
two-dimensional networks. This was consistent with SAED and
compositional analyses of deposited TiO.sub.2 films indicating a
mixture of polycrystalline anatase and rutile and of the same
mixture plus fcc Pt nanoparticles (FIG. 30, plate (b)),
respectively. Pt crystalline particles with 1 to 5 nm size were
randomly distributed on the surfaces of TiO.sub.2 islands and
sometimes were partially coalesced forming elongated aggregates. In
the latter case, significant thickness of the GaN NWs made it
difficult to visualize TiO.sub.2 deposits due to the limited
contrast difference between TiO.sub.2 and GaN and presence of
multiple heavy Pt particles. In spite of these limitations,
detailed HRTEM and HR-STEM observations revealed 0.35 nm (101) hcp
lattice fringes belonging to anatase (see FIG. 30, plate (b), upper
left inset) and 0.23 nm to 0.25 nm (111) and 0.20 nm to 0.22 nm
(200) fcc lattice fringes belonging to Pt nanocrystallites,
respectively, as well as amorphous-like Pt clusters with diameters
around 1 nm or less (see FIG. 31, plates (a) and (b)).
In the FIG. 31, HAADF-STEM image shows 1 nm to 5 nm diameter bright
Pt nanoparticles and barely visible TiO.sub.2 islands (medium grey)
randomly distributed near the edge of the nanowire. The presence of
both TiO.sub.2 and Pt nanocrystallites was confirmed by the
analysis of selected areas using XEDS nanoprobe capabilities.
Current-Voltage (I-V) Characteristics of NWNC Hybrids in Dark
FIG. 32 shows the I-V characteristics of the GaN/(TiO.sub.2--Pt)
and GaN/Pt hybrid sensor devices at different stages of processing.
A plan-view SEM image of an exemplary sensor device is shown in the
inset of FIG. 32, plate (b) for representation purposes. The I-V
curves of the as-fabricated GaN NW two-terminal devices were
non-linear and asymmetric. A small increase in the positive current
after the deposition of TiO.sub.2 nanoclusters (curve 2) can be
attributed to decreased surface depletion of the GaN NW due to
passivation of surface states, and/or the high temperature
deposition (325.degree. C.) of the nanoclusters initiating ohmic
contact formation. The devices annealed at 700.degree. C. for 30 s
after the deposition of TiO.sub.2 NCs showed significant change in
their I-V characteristics with a majority of the devices exhibiting
linear I-V curves. Interestingly, Pt NC deposition on TiO.sub.2
coated GaN NWs further increased the conductivity of the nanowire.
This is due to the fact that the Pt clusters depleted the TiO.sub.2
clusters by removing free electrons. Increased depletion in the
TiO.sub.2 clusters due to Pt would decrease TiO.sub.2 induced
depletion in the GaN NW, leading to an increase in the NW current.
With the Pt/GaN hybrids, the current decreases followed by the
deposition of Pt (see FIG. 32, plate (b)) as expected due to the
depletion region formed in the NW under the metal clusters.
The nature of the depletion region formed by the nano-sized metal
clusters on a semiconductor may be determined by Zhdanov's model.
FIG. 33 shows the calculated zero-bias depletion depth produced in
GaN and TiO.sub.2 respectively, as a function of the Pt cluster
radius according to Equation (1). For calculating the depletion
depth we assumed the effective conduction band density of states in
TiO.sub.2 as 3.0.times.10.sup.21 cm.sup.-3 and point-defect related
donor concentration as 1.0.times.10.sup.18 cm.sup.-3 [43,44]. The
electron concentration in the GaN NWs was measured to be
1.times.10.sup.17 cm.sup.-3 in a separate experiment.
FIG. 33 indicates that even a single Pt NC of 2 nm radius can
significantly deplete a 10 nm (average size) TiO.sub.2 cluster. The
effect of TiO.sub.2 depletion on GaN NW is difficult to determine
as it could be influenced by numerous factors including interface
states and particle geometry. Given the very high density of
TiO.sub.2 clusters on the NW surface (see FIG. 31, plate (b)), it
is clear that the Pt particles mostly reside on the surfaces of
TiO.sub.2 NCs. However, from FIG. 33 we can see that when Pt NCs
are directly on GaN, they deplete the carriers in an even larger
region in the GaN NW. This qualitatively explains the relatively
larger change in current observed when Pt NCs were deposited on
bare GaN NWs as compared to the change in current when Pt NC were
deposit on the TiO.sub.2-coated NWs.
Comparative Sensing Behavior of GaN/(TiO.sub.2--Pt), GaN/Pt and
GaN/TiO.sub.2 NWNC Hybrid Sensors
The photocurrent through the bare GaN NW devices did not change
when exposed to different chemicals mixed in air, even for
concentrations as high as 3%. In contrast, the TiO.sub.2-coated
hybrid devices responded even to the pulses of 20 sccm airflow in
the presence of UV excitation. The response of the TiO.sub.2
NC-coated GaN nanowire hybrid sensors to different concentrations
of benzene, toluene, ethylbenzene, chlorobenzene, and xylene in air
is discussed above. The GaN/TiO.sub.2 hybrids showed no response
when exposed to other chemicals such as alcohols, ketones, amides,
alkanes, nitro/halo-alkanes, and esters.
Remarkably, after the deposition of Pt nanoclusters on the
GaN/TiO.sub.2 hybrids, the sensors were no longer sensitive to
benzene and other aromatic compounds, but responded only to
hydrogen, methanol, and ethanol. In addition, the
GaN/(TiO.sub.2--Pt) hybrids showed no response when exposed to
higher carbon-containing (C>2) alcohols such as n-propanol,
iso-propanol, and n-butanol. FIG. 5 shows the change of
photocurrent of a GaN/(TiO.sub.2--Pt) sensor in the presence of 20
sccm air flow of air mixed with 1000 .mu.mol/mol (ppm) of methanol,
ethanol, and water, respectively, and 20 sccm of nitrogen flow
mixed with 1000 .mu.mol/mol (ppm) hydrogen. The change in the
photocurrent of the sensor when 20 sccm of breathing air is flowing
through the test chamber serves as a reference for calculating the
sensitivity of the sensors. The sensitivity is defined as
(R.sub.gas-R.sub.air)/R.sub.air, where R.sub.gas and R.sub.air are
the resistances of the sensor in the presence of the analyte-air
mixture and in the presence of air only, respectively (R.sub.air is
replaced with R.sub.nitrogen for hydrogen sensing experiments).
The GaN/TiO.sub.2 hybrids without Pt showed no response to hydrogen
and the alcohols. Interestingly, when Pt NC-coated GaN NW hybrids
(GaN/Pt) with the same nominal thickness were tested, they showed
very limited sensitivity only to hydrogen and not to any alcohols.
The comparative summary of the sensing behavior of the three
different hybrids are presented in FIG. 34.
The response of the GaN/(TiO.sub.2--Pt) NWNC sensor to different
concentrations of methanol in air is shown in FIG. 35, plate (a).
FIG. 35, plate (b) shows the response to different concentrations
of hydrogen in nitrogen for the same GaN/(TiO.sub.2--Pt) NWNC
sensor device. The sensor response is much higher for hydrogen
compared to methanol and ethanol. The response time is also much
shorter for hydrogen as compared to methanol, and the sensor
photocurrent saturates after initial 20 s exposure.
The response time was defined as the time taken by the sensor
current to reach 90% of the response (I.sub.f-I.sub.0) when exposed
to the analyte. The I.sub.f is the steady sensor current level in
the presence of the analyte, and I.sub.0 is the current level
without the analyte, which in our case is in the presence of 20
sccm of air flow. The recovery time is the time required for the
sensor current to recover to 30% of the response (I.sub.f-I.sub.0)
after the gas flow is turned off (see Garzella C et al. (2000)
Sensors and Actuators B: Chemical 68:189-196). The response time
for hydrogen was .apprxeq.60 seconds, whereas the response time for
ethanol and methanol was 80 seconds. The sensor recovery time for
hydrogen was .apprxeq.45 seconds and the recovery times for
ethanol, methanol was .apprxeq.60 seconds and .apprxeq.80 seconds,
respectively. For comparison, Wang et al. demonstrated a
conventional ZnO NW-based hydrogen sensor with a response time of
10 minutes for 4.2% sensitivity (Wang H T et al. (2005)
"Hydrogen-selective sensing at room temperature with ZnO nanorods,"
Appl. Phys. Lett. 86:243503).
The sensitivity plot of a GaN/(TiO.sub.2--Pt) hybrid device for the
various analytes tested is shown in FIG. 36, plate (a). Note that
the lowest concentration detected for methanol and hydrogen (1 ppm
or .mu.mol/mol) is not the sensor's detection limit, but a system
limitation. It can be seen that the sensor is more sensitive to
methanol than ethanol for concentrations.gtoreq.1000 .mu.mol/mol
(ppm), and the relative sensitivity switches for concentrations of
500 .mu.mol/mol (ppm) and below. Similar behavior is observed with
twenty unique devices, possibly due to difference in surface
coverage of the different alcohols over the concentration range.
FIG. 36, plate (b) is a comparative plot showing the sensitivity of
GaN/(TiO.sub.2--Pt) and GaN/Pt hybrid sensors to hydrogen in
nitrogen. The GaN/Pt hybrid devices showed relatively low
sensitivity with detection limit of 50 .mu.mol/mol (ppm), below
which the devices stopped responding. The gas exposure time was
also increased to 200 seconds for the GaN/Pt devices to obtain
increased response compared to 100 seconds for the
GaN/(TiO.sub.2--Pt) GaN devices. The sensitivity of the
GaN/(TiO.sub.2--Pt) sensors was greater for alcohols and hydrogen
when compared with the same concentrations of water in air, which
thus enables their use in high-humidity conditions.
Table X and Table XI compare the performance of the sensor devices
of the present invention with sensors disclosed in the most recent
literature in terms of operation temperature, carrier gas, lower
detection limit, and response/recovery times. The comparison
indicates that the sensors devices of the present invention exhibit
an excellent response to very low concentrations of analytes (100
ppb for ethanol and 1 ppm for hydrogen) at room temperature, with
air as the carrier gas. The testing conditions closely resembled
real-life conditions, which underlines the significance of the
disclosed sensors. The response and recovery times were also lower
for the disclosed sensors compared to the other conventional
sensors, as shown in Tables X and XI.
TABLE-US-00010 TABLE X Performance of GaN/(TiO.sub.2--Pt) NWNC
hybrid sensors to ethanol in comparison with conventional sensors
Response/ Lower Carrier Testing Recovery Time Detection Limit Gas
Temperature Sensor of Present 80 s/75 s 100 ppb with air Room
temperature Invention 1% sensitivity.sup.4 (RT) CNT.sup.1/SnO.sub.2
core shell 1 s/10 s 10 ppm air 300.degree. C. nanostructures
MWCNTs.sup.2/ 20 s/20 s 18,000 ppm air RT NaClO.sub.4/polypyrrole
Metal-CNT hybrids ~2 min/ 500 ppb with N.sub.2 in a vacuum RT
(recovery time sensitivity <1% test chamber not reported)
V.sub.2O.sub.5 nanobelts 50 s/50 s 5 ppm air 150.degree.
C.-400.degree. C. ZnO nanorods 3.95 min/5.3 min 10 ppm Synthetic
air 125.degree. C.-300.degree. C. ZnO nanowires 10 s/55 s 1 ppm air
220.degree. C. ITO.sup.3 nanowires 2 s/2 s 10 ppm air 400.degree.
C. SnO.sub.2 nanowires 2 s/2 s 10 ppm air 300.degree. C.
.sup.1Carbon nanotubes .sup.2Multiwall carbon nanotubes
.sup.3Indium tin oxide .sup.4Sensitivity values for sensors with
lowest limit similar to disclosed results were compared.
TABLE-US-00011 TABLE XI Performance of GaN/(TiO.sub.2--Pt) NWNC
hybrid sensors to hydrogen in comparison with conventional sensors
Response/ Lower Testing recovery times detection limit Temperature
Sensor of Present 60 s/45 s 1 ppm with RT Invention sensitivity of
4% CNT films 5 min/30 s .sup. 10 ppm RT SWCNT/SnO.sub.2 2 s/2 s 300
ppm 250.degree. C. Pd/CNTs 5 min/5 min 30 ppm with RT sensitivity
of 3% Pd/Si NWs .sup. 1 hr/50 min 3 ppm RT Pt doped SnO.sub.2 NWs 2
min/10 min 100 ppm 100.degree. C.
The present results indicate the unique ability to tailor the
selectivity of NWNC chemical sensors. With infinite combinations of
metal and metal-oxide composite clusters available, there is a huge
potential for sensor designs targeted for a multitude of
applications.
Example 3
Alcohol sensors using gallium nitride (GaN) nanowires (NWs)
functionalized with zinc oxide (ZnO) nanoparticles are
demonstrated. These sensors operate at room temperature, are fully
recoverable, and demonstrate a response and recovery time on the
order of 100 seconds. The sensing is assisted by UV light within
the 215-400-nm band and with the intensity of 375 nW/cm.sup.2
measured at 365 nm. The ability to functionalize an inactive NW
surface, with analyte-specific active metal-oxide nanoparticles,
makes this sensor suitable for fabricating multianalyte sensor
arrays.
Methods and Materials
Si-doped c-axis n-type GaN NWs were grown using catalyst-free
molecular beam epitaxy on Si (III) substrate as described in
Bertness K A et al. (2008), supra, J. Cryst. Growth
310(13):3154-3158. The NW diameter and length were in the ranges of
250-350 nm and 21-23 .mu.m, respectively. The GaN NWs were detached
from the substrate by sonication in isopropanol and
dielectrophoretically aligned across the pre-patterned electrodes.
The electrodes were fabricated using photolithography followed by
deposition of a metal stack of Ti (40 nm)/Al (420 nm)/Ti (40 nm).
Thick bottom electrodes ensure the free suspension of the NWs. For
the formation of ohmic contacts to the NW ends, the top metal
contacts were fabricated using a metal stack of Ti (70 nm)/Al (70
nm)/Ti (40 nm)/Au (40 nm), as described in A. Motayed et al.
(2003), supra, J. Appl. Phys. 93(2):1087-1094. Rapid thermal anneal
(RTA) was performed at 700.degree. C. for 30 seconds in argon
atmosphere to promote the formation of ohmic contacts and to reduce
the stress in the thick bottom electrodes. Finally, ZnO
nanoparticles were sputter deposited on the NW device with an RF
power of 300 W in 60 standard cubic centimeters per minute (sccm)
of oxygen and 40 sccm of argon gas flow at room temperature.
Deposition time of 160 seconds was found to be optimal for the
formation of uncoalesced oxide nanoparticles.
The microstructure of the devices was characterized using a
scanning electron microscope (SEM) and X-ray diffraction (XRD). Due
to the small size of the nanoparticles, the XRD signal from ZnO was
not detected. Thus, the analysis was performed on a 300-nm-thick
ZnO film sputter deposited on Si (111) substrate with the
assumption that the ZnO crystallinity is similar for nanoparticles
and for thin films deposited at the identical conditions.
Current-voltage characteristics of the devices were also measured
to determine the nature of the NW-metal contacts.
For the gas sensing measurements, a device was placed inside the
stainless steel chamber with an inlet and an outlet for the analyte
vapors. The chamber, with a volume of 0.73 cm.sup.3, has a quartz
window on the top to facilitate exposure of the device to UV light.
The wavelength of the light bulb was confined to the range of
215-400 nm; the intensity recorded at 365 nm was 3.75 nW/cm.sup.2.
The sensor baseline was established at a constant flow of 40 sccm
of breathing air under illumination. For sensing experiments, 40
sccm of the mixture of the breathing air and analyte vapor was
passed through the chamber. All sensing measurements were performed
in the presence of UV light and 5-V dc voltage bias applied across
the device terminals. Negligible or no chemiresistive response was
observed for all the chemicals in the absence of the
illumination.
Results and Properties
FIG. 6, plate (a) shows a SEM image of a device with a single GaN
NW suspended across the metal electrodes. FIG. 6, plate (b) shows
the ZnO nanoparticles on the facets of a GaN NW. The
current-voltage characteristics of the device measured before and
after RTA are shown in FIG. 6, plate (c). As shown in FIG. 6, plate
(d), XRD reveals that the sputter-deposited ZnO is crystalline and
highly (0002) textured.
Referring to FIG. 8 sensor response to air and nitrogen was
evaluated. FIG. 8, plate (a) shows the device response to the
different flow rates of breathing air. As seen therein, device
conductance decreases upon exposure to the breathing air, and the
decrease is proportional to the flow rate. Opposite behavior (i.e.,
an increase in conductivity) is observed when the device is exposed
to nitrogen gas as seen in FIG. 8, plate (b).
Referring to FIG. 7, sensor response to alcohols and other analytes
was evaluated. When exposed to alcohol vapors (methanol, ethanol,
n-propanol, isopropanol, n-butanol, and isobutanol), the devices
showed an increase in conductivity with maximum sensitivity toward
methanol. FIG. 7 shows the device response to 500-.mu.mol/mol (ppm)
methanol vapor in breathing air.
For the isomers of an alcohol, the sensitivity decreases with
branching in the carbon chain. Hence, as shown in FIG. 7 (inset,
bottom left), the sensitivity toward isobutanol is less than that
toward n-butanol. As shown in FIG. 7 (inset, bottom right), the
devices show a negligible response to possible interfering
chemicals such as benzene and hexane, whereas the sensitivity
toward 100 .mu.mol/mol (ppm) of ethanol is similar to the
sensitivity toward 1000 .mu.mol/mol (ppm) of acetone. Ethanol vapor
concentration down to 100 .mu.mol/mol (ppb) was successfully
detected, and the detection of even lower concentrations is
possible with alternative measurement setup.
Example 4
A hybrid chemiresistive architecture, utilizing nanoengineered
wide-bandgap semiconductor backbone functionalized with
multicomponent photocatalytic nanoclusters of metal-oxides and
metals was demonstrated. These sensors operated at room-temperature
via photoenabled sensing.
Etching of Semiconductor Nanostructures
For real-time nanosensors, successful etching of semiconducting
nanostructures, which is characterized by smooth surfaces with
minimal sub-surface damage and appropriate side-wall profiles, is
desired. This requires overcoming the strong chemical bond energy
in widegap semiconductors, and also adjusting the process
conditions to overcome inherent defects in epitaxially grown films
on non-native substrates using heteroepitaxy. Otherwise, an
un-optimized etching process may result in surface morphologies
that include pits and/or pillars.
An Inductively Coupled Plasma-Reactive Ion Etching (ICP-RIE)
process with Cl.sub.2/Ar/N.sub.2 chemistry is provided, with an
etch rate of about 100 nm/min for GaN. The dry etching process may
be optimized using X-ray photoelectron spectroscopy (XPS), scanning
electron microscopy (SEM), photoconductivity measurements, and
photoluminescence (PL) measurements.
Fabrication Detail
Prior to dry etching, semiconductor wafer surfaces are treated with
standard RCA cleaning procedures. As a mask for selective etching,
a 500-nm-thick SiO.sub.2 film is deposited by standard
plasma-enhanced chemical vapor deposition (PECVD). Etching patterns
are defined by deep UV lithography using a proximity aligner
capable of generating 300 nm feature sizes. Electron beam
deposition of Ni (.about.20 nm) followed by lift-off is carried out
to complete the formation of mask for the SiO.sub.2 etch.
Direct metal-masking of the semiconductor is not done in order to
avoid un-intentional doping of the metal during the etch process.
The ICP-RIE etching is performed using the following procedure. GaN
etch is accomplished using ICP etching with a Cl.sub.2/N.sub.2/Ar
(25:5:2) gas mixture under a pressure of 5 mTorr with varying ICP
etching power and radio frequency (RF) power. For nitrides,
Chlorine-based etches are used because it has been shown to produce
vertical sidewalls due to the ion assisted etching mechanism with
smooth profiles. Temperature of the etch is a parameter that
provides control of the sidewall angle. With low-temperature etch,
the sub-surface damage may also be controlled.
Each sample is treated with a standard RCA clean before the
activation annealing, the etching, and the measurements. Etching
profile and surface morphology may be investigated by SEM. The
surface chemical properties of semiconductor after the etch is
characterized using an XPS system and PL measurements performed at
room temperature. The electrical properties of etched semiconductor
backbone are characterized photocurrent measurements. Photocurrent
intensity is a direct measure of the surface recombination, i.e.,
higher photocurrent intensity will indicate less surface defect
non-radiative recombination, hence less sub-surface damage. For
GaN, Ti/Al/Ti/Au (70 nm/70 nm/50 nm/50 nm) ohmic electrodes are
formed at both ends of the backbone nanostructures and then
annealed at temperatures from 500 C to 800 C for .about.1 min. The
nanodevices are then functionalized with different metal and
metal-oxide nanoclusters using reactive sputtering.
A schematic representation of an exemplary fabrication flow for
semiconductor-nanocluster based gas sensors according to the
present invention is shown in FIG. 37. As shown, the fabrication
flow provides for parallel architecture, with multiple parallel
sections. The multi-analyte arrays can be created on one single
chip (10 mm.times.10 mm) by depositing clusters of different
components on different micro-scale devices. This is possible due
to low-temperature sputtering process used for the cluster
deposition. An array of multiple sensors (e.g. for detecting
NO.sub.x, SO.sub.x, CO.sub.x, NH.sub.3, and H.sub.2O) may be
fabricated all on one single chip. FIG. 38 shows exemplary
inter-digitated GaN devices on Si and sapphire substrates formed
using top-down processes (e.g., such as shown in FIG. 37).
Example 5
Protection against explosive-based terrorism may be achieved by
large-scale production of nano-sensor arrays that are inexpensive,
highly sensitive and selective with low response and recovery
times. In this study, the selective response of GaN
nanowire/TiO.sub.2 nanocluster hybrids to nitroaromatic explosives,
including trinitrotoluene (TNT), dinitrotoluene (DNT), nitrotoluene
(NT), dinitrobenzene (DNB) and nitrobenzene (NB) at room
temperature is demonstrated. The sensors detected between 0.5 ppb
and 8 ppm TNT with good selectivity against interfering compounds
such as toluene. The sensitivity of 1 ppm of TNT is .apprxeq.10%
with response and recovery times of =30 seconds.
N-type (Si doped) GaN nanowires functionalized with TiO.sub.2
nanoclusters were utilized for selectively sensing nitro-aromatic
explosive compounds. GaN is a wide-bandgap semiconductor (3.4 eV)
with unique properties. Its chemical inertness and capability of
operating in extreme environments (high-temperatures, presence of
radiation, extreme pH levels) is highly desirable for sensor
design. TiO.sub.2 is a photocatalytic semiconductor with bandgap
energy of 3.2 eV (anatase phase). The TiO.sub.2 nanoclusters were
selected to act as nanocatalysts to increase the sensitivity, lower
the detection time, and enable the selectivity of the structures to
be tailored to a target analyte (e.g., the most common explosives,
trinitrotoluene (TNT) and other nitro-aromatics).
Materials and Methods
GaN nanowires were grown by Molecular Beam Epitaxy method as
described in Bertness K A et al. (2008), supra, J. Crystal Growth
310(13):3154-3158. The nanowires are aligned on a pre-patterned
substrate using dielectrophoresis. Details of the device
fabrication are reported in Aluri G S et al. (2011) "Highly
selective GaN-nanowire/TiO.sub.2-nanocluster hybrid sensors for
detection of benzene and related environment pollutants,"
Nanotechnology 22(29):295503. After fabrication of two-terminal GaN
NW devices, the TiO.sub.2 NCs were deposited on the GaN NW surface
using RF magnetron sputtering. The deposition was done at
325.degree. C. with 50 standard cubic centimeters per minute (sccm)
of Ar flow, and 300 W RF power. The nominal deposition rate was
about 0.24 .ANG./s. Thermal annealing of the complete sensor
devices (GaN NW with TiO.sub.2 nanoclusters) was done at
700.degree. C. for 30 seconds in a rapid thermal processing system.
The device substrates, i.e., the sensor chips, were wire-bonded on
a 24 pin ceramic package for the gas sensing measurements.
The microstructure and morphology of the sputtered TiO.sub.2 films
used for the fabrication of the sensors were characterized by
high-resolution transmission and scanning transmission electron
microscopy (HRTEM/STEM), selected-area electron diffraction (SAED),
and field-emission scanning electron microscopy (FESEM). For the
TEM characterization, the GaN NWs were dispersed on 10 nm thick
carbon films supported by Mo-mesh grids, followed by the deposition
of TiO.sub.2 NCs and annealing and subsequent Pt deposition. The
samples were analyzed in a FEI Titan 80-300 TEM/STEM microscope
operating at 300 kV accelerating voltage and equipped with S-TWIN
objective lenses, which provided 0.13 nm (STEM) and 0.19 nm (TEM)
resolution by points. The instrument also had a Gatan CCD image
acquisition camera, bright-field (BF), ADF and high-angle annular
dark-field (HAADF) STEM detectors to perform spot, line profile,
and areal compositional analyses using an EDAX 300 kV
high-performance Si/Li X-ray energy dispersive spectrometer
(XEDS).
The as-fabricated sensors were placed in a custom designed gas
chamber for gas exposure measurements. Detailed description of the
experimental setup and experimental conditions is provided in Aluri
G S et al. (2011), supra, Nanotechnology 22(29):295503. The device
characterization and the time dependent sensing measurements were
done using an Agilent B1500A semiconductor parameter analyzer. The
gas sensing experiments were performed by measuring the electrical
conductance of the devices upon exposure to controlled flow of
air/chemical mixture in presence of UV excitation (25 W deuterium
bulb operating in the 215 nm to 400 nm range). For all the sensing
experiments with chemicals, breathing air (<9 .mu.mol/mol of
water) was used as the carrier gas. After the sensor devices were
exposed to the aromatic compounds, they were allowed to regain
their baseline current with the air-chemical mixture turned-off,
without purging or evacuating the test-chamber.
Results
Morphological and Structural Characterization of NWNC Hybrids
TEM imaging was conducted under minimal beam intensity conditions
close to the Scherzer defocus at highest available accelerating
voltage of 300 kV using both stationary beam (bright-field
TEM/SAED, phase-contrast high-resolution TEM) and scanning beam
(STEM/XEDS) modes. Areas for analyses were selected near the wire's
edges and on the amorphous carbon support film in the vicinity of
the NWs. FIG. 39 shows HRTEM micrographs of a GaN NW on a thin
amorphous carbon support films with TiO.sub.2 coating. The
deposited TiO.sub.2 layer formed an island-like film, where 10 nm
to 50 nm partially aggregated particles (circled areas in FIG. 39)
were often interconnected into extended two-dimensional networks.
This was consistent with SAED and compositional analyses of
deposited TiO.sub.2 films indicating a mixture of polycrystalline
anatase and rutile phases. Despite the limited contrast difference
between TiO.sub.2 and GaN, detailed HRTEM and HR-STEM observations
revealed 0.35 nm (101) hcp lattice fringes belonging to
anatase.
Current-Voltage (I-V) Characteristics of NWNC Hybrids
Referring to FIG. 40, I-V characteristics of a GaN NW two-terminal
device at different stages of processing are shown. The I-V curves
of the as-deposited devices were non-linear and asymmetric (with a
low current of 35 nA). However, the current increased (to a 100 nA)
with the deposition of TiO.sub.2 nanoclusters. This may be
attributed to decreased surface depletion of the GaN NW due to
passivation of surface states, and/or the high temperature
deposition (325.degree. C.) of the nanoclusters initiating ohmic
contact formation. The devices annealed at 700.degree. C. for 30
seconds showed significant changes in their I-V characteristics
with a majority of the devices exhibiting linear I-V curves. This
is consistent given low resistance ohmic contacts to the nitrides
require annealing at 700.degree. C.-800.degree. C.
Sensing Behavior of GaN/TiO.sub.2 NWNC Hybrid Sensors
The photocurrent through the bare GaN NW devices did not change
when exposed to different chemicals mixed in air, even for
concentrations as high as 3%. In contrast, the TiO.sub.2-coated
hybrid devices responded even to the pulses of 20 sccm airflow in
the presence of UV excitation. The response of the TiO.sub.2
NC-coated GaN nanowire hybrid sensors to different concentrations
of benzene, toluene, ethylbenzene, chlorobenzene, and xylene in air
is discussed above. The GaN/TiO.sub.2 hybrids showed no response
when exposed to other chemicals such as alcohols, ketones, amides,
alkanes, nitro/halo-alkanes, and esters.
The response of the TiO.sub.2 coated hybrid devices when exposed to
a concentration of 100 ppb of the aromatics and nitro-aromatics in
air can is shown in FIG. 41, plate (a). The photocurrent for these
sensors increased with respect to air when exposed to toluene
vapors, whereas for every other aromatic compound the photocurrent
decreased relative to air. The response is observed to increase
with the increase in the number of nitro groups attached to the
aromatic compound. The response of the hybrid device to different
concentrations of TNT in air from 8 ppm down to as low as 500 ppt
is shown in FIG. 41, plate (b). The response time is defined as the
time taken by the sensor current to reach 90% of the response
(I.sub.f-I.sub.0) when exposed to the analyte. The I.sub.f is the
steady sensor current level in the presence of the analyte, and
I.sub.0 is the current level without the analyte, which in this
case is in the presence of air. The recovery time is the time
required for the sensor current to recover to 30% of the response
(I.sub.f-I.sub.0) after the gas flow is turned off. The response
and recovery times of the nano-devices to different concentrations
of TNT are .apprxeq.30 seconds. The response and recovery times of
the rest of the compounds varied from .apprxeq.60 seconds to
.apprxeq.75 seconds.
The sensitivity is defined as (R.sub.gas-R.sub.air)/R.sub.air,
where R.sub.gas and R.sub.air are the resistances of the sensor in
the presence of the chemical-air mixture and in presence of air,
respectively. The sensitivity plot of a hybrid device for the
different aromatics and nitro-aromatics tested is shown in FIG. 42.
The sensitivity ((R.sub.gas-R.sub.air)/R.sub.air) for 1 ppm of TNT
is .apprxeq.10%. The devices exhibit a very highly sensitive and
selective response to TNT when compared to interfering compounds
like toluene. Toluene shows an increase in response with respect to
air, whereas TNT shows a decrease when compared to air. The plot
identifies the sensor's ability to sense wide concentration ranges
of the indicated chemicals. The sensitivity of two different
devices (device 1--D1; device 2--D2) to the different aromatic
compounds can be seen in FIG. 43.
As discussed above, oxygen vacancy defects (Ti.sup.3+ sites) on the
surface of TiO.sub.2 are the "active sites" for the adsorption of
species like oxygen, water, and organic molecules. In the presence
of UV excitation with an energy above the bandgap energy of anatase
TiO.sub.2 (3.2 eV) and GaN (3.4 eV), electron-hole pairs are
generated both in the GaN NW and in the TiO.sub.2 cluster.
Photogenerated holes in the nanowire tend to diffuse towards the
surface due to surface band bending. This effect of separation of
photogenerated charge carriers results in a longer lifetime of
photogenerated electrons, which in turn enhances the photoresponse
of the nanowire devices in general. Since the nitro-aromatic
compounds are highly electronegative, they tend to attract
electrons from other molecules through charge transfer. This charge
transfer between the adsorbed species on the TiO.sub.2 nanocluster,
and the nitro groups in the nitro-aromatic compounds increases the
width of the depletion region in the nanowire device, reducing the
current.
The potential of the disclosed nanostructure-nanocluster hybrids
for next-generation nano-sensors having the capability to detect
explosive compounds quickly and reliably is clearly demonstrated.
The GaN/TiO.sub.2 nanowire nanocluster hybrid devices tested
detected trace amounts of aromatic and nitro-aromatic compounds in
air at room temperature with very low response and recovery times
(.apprxeq.30 seconds). The nitro-aromatic explosives like TNT are
selectively detectable even for concentrations as low as 500
ppt.
Example 6
Nitrogen dioxide (NO.sub.2) sensors using gallium nitride (GaN)
nanowires (NWs) functionalized with titanium dioxide (TiO.sub.2)
nanoclusters are demonstrated. Exemplary sensor fabrication
methodologies are described above (e.g., see Example 1 & FIG.
19).
FIG. 44, plate (a) illustrates the dynamic responses of the
TiO.sub.2 based sensor exposed to 250 ppm NO.sub.2 mixed with
breathing air under UV illumination and dark, and at room
temperature. For each cycle, the gas exposure time was 300 s. FIG.
44, plate (b) illustrates change in resistance under UV at mixtures
of 100 ppm, 250 ppm, and 500 ppm with breathing air, with the inset
showing the measured responses under UV as a function of NO.sub.2
concentrations with uncertainty. Sensitivity S is presented by
(I.sub.g-I.sub.a).times.100/I.sub.a, wherein I.sub.g is the device
current in the presence of an analyte in breathing air and Ia is
the current in pure breathing air, both measured 300 s after the
flow is turned on. FIG. 45 illustrates schematically an NO.sub.2
gas sensing mechanism of the TiO.sub.2 sensor under UV illumination
and at room temperature. FIG. 45, plate (a) shows the mechanism in
a dark environment with breathing air in. FIG. 45, plate (b) shows
the mechanism under UV illumination in breathing air. FIG. 45,
plate (c) shows the mechanism under UV illumination with a mixture
of NO.sub.2 and breathing air.
The response of the TiO.sub.2 based sensor exposed to 500 ppm
NO.sub.2 under UV illumination and under dark at room temperature
is shown in FIG. 46. As described, the UV illumination allows for
efficient photodesorption of adsorbed oxygen and hydroxyl species,
thus introducing additional oxide surface sites or receptors for
adsorption of target molecules. Photocatalytic reactions then occur
between the adsorbed target molecules and the photo carriers in the
oxide sites, leading to a modification of the surface potential and
semiconductor backbone current change (transduction). The
photodesorption of the adsorbed target molecules and reaction
species leads to a reversal of photocurrent to baseline
(recovery).
A GIXRD scan of thermally processed ultrathin TiO.sub.2 film is
shown in FIG. 47, plate (a). Optical properties (bandgap) are
illustrated in FIG. 47, plate (b).
Example 7
Carbon dioxide (CO.sub.2) sensors using gallium nitride (GaN)
nanowires (NWs) functionalized with tin oxide and copper oxide
(SnO.sub.2--CuO) nanoclusters are demonstrated. Exemplary sensor
fabrication methodologies are described above.
FIG. 48, plate (a) illustrates schematically a SnO.sub.2--Cu
nanocluster CO.sub.2 sensor, including an electrode disposed on a
sapphire substrate, and GaN NWs functionalized with SnO.sub.2
nanoclusters and SnO.sub.2--CuO nanoclusters. AFM images of the
SnO.sub.2--Cu nanocluster CO.sub.2 sensor are shown in FIG. 48,
plates (b) and (c). FIG. 49 illustrates the dynamic response of the
SnO.sub.2--Cu based sensor exposed to CO.sub.2 at room temperature
for various concentrations. FIG. 50 illustrates graphically the
response of the SnO.sub.2 based sensor at different relative
humidity (RH) concentrations at room temperature.
All publications and patents mentioned in this specification are
herein incorporated by reference to the same extent as if each
individual publication or patent application was specifically and
individually indicated to be incorporated by reference in its
entirety. While the invention has been described in connection with
specific embodiments thereof, it will be understood that it is
capable of further modifications and this application is intended
to cover any variations, uses, or adaptations of the invention
following, in general, the principles of the invention and
including such departures from the present disclosure as come
within known or customary practice within the art to which the
invention pertains and as may be applied to the essential features
hereinbefore set forth.
* * * * *